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Km RESEARCH REFERENCE CfllLECTIO' f: @S NATIONAL CENTER, MS-521
UNITED STATES i""' DEPARTMENT OF THE INTERIOR
GEOLOGICAL SURVEY
22002
SUMMARY TABLES FOR SELECTED DIGITAL IMAGE PROCESSING SYSTEMS
Open-File Report 77-414
UNITED STATESDEPARTMENT OF THE INTERIOR
GEOLOGICAL SURVEY
SUMMARY TABLES FOR SELECTED DIGITAL IMAGE PROCESSING SYSTEMS
By Virginia Qarter, U.S. Geological SurveyFrederic fill ingsley, Get Propulsion Laboratory Jeannine Lamar, Rand Corporation
Open-File Report 77-414
mw
1977
CONTENTS
Page
Abstract 1
Introduction 1
System Summaries 3
G.E. Image-100 3
Bendix MDAS 4
I 2S System 101 4
ESL Idims 5
Comtal Series 9 5
ISI System 470 and Sand 6
Kandidats 6
JPL Vicar 7
Purdue Larsys 7
Tables 9
Definitions 36
General purpose image processing 36
Radiometric corrections 36
Digital level slicing 37
Contrast stretch 37
Geometric corrections 37
Geometric warping 37
Registration 38
Page
Geometric interpolation techniques 38
Filtering 38
Transforms 39
Multispectral analysis 39
Supervised classifier 39
Unsupervised classifier 40
Mensuration 41
Inter-band manipulations 41
Statistical operations 41
Inputs 42
TV camera 42
Microdensitometer 42
Digital tapes 42
Analog tapes 43
Outputs 43
Volatile outputs 43
Hard copy outputs 43
Other features 43
Microprogrammable processor 44
Present computer 44
Software 44
n
TABLES
Page Table 1. General purpose image processing 9
2. Multispectral classification 18
3. System inputs 24
4. System outputs 27
5. Other system features 33
SUMMARY TABLES FOR SELECTED DIGITAL IMAGE PROCESSING SYSTEMS
By
Virginia Carter Frederic Billingsley Jeannine Lamar
ABSTRACT
The exploration of earth from space has greatly increased the demand for
computer systems of great speed and complexity.
Because it has proved difficult to make comparisons between systems in an
orderly fashion, a set of five tables have been developed for the comparison
of digital image processing systems. The tables have been compiled for six
U.S. manufactured hardware/software systems. Three U.S. software systems
are included in the tables also.
The tables and the System Summaries have been prepared primarily from in
formation supplied by the manufacturers. While some rewording has been
done to make the descriptions parallel, the manufacturers' wording has been
retained to a large extent.
INTRODUCTION
The exploration of Earth from space has greatly increased the demand for
computer systems of great speed and complexity. Among the many functions
of these computer systems is the processing of digital images such as those
produced by Landsat (formerly Earth Resources Xecnn°l°9y Satellite - ERTS).
There has been a proliferation of digital image processing systems, both
hardware/software and software, to analyze these data.
Because it has proved difficult to make comparisons between systems in an
orderly fashion, a set of five tables have been developed for the comparison
of digital image processing systems. The tables have been compiled for six
U.S. manufactured hardware/software systems: 1) the General Electric (GE)
IMAGE-100, 2) the Bendix Multispectral Data Analysis System (MDAS), 3) the
Electronics Systems Laboratory (ESL) Interactive Digital Image Manipulation
System (IDIMS), 4) the Comtal Corporation (CC) Series 9 System, 5) the
International Imaging Systems, Inc. (I 2S) System 101, and 6) the Interpreta
tion Systems Incorporated (ISI) System 470.
Three U.S. software systems are i
Propulsion Laboratory (JPL) Video
2) the Laboratory for Applications of
3) the University of Kansas KANDIDATS
rapidly, and other systems may be add
included in the tables also: 1) the Jet
Communication and Retrieval (VICAR) System,
Remote Sensing (LARS) System, and
System. The tables can be updated
5d using the same tabular format.
Isolated pieces of hardware performing
single purpose systems where processing
are not included.
These tables are intended for system
There are many existing digital image
different in concept or operation,
these tables, nor can there ever be,
a system for a particular use. The
subjective judgements on the systems,
to take into account such parameters
only part of a system function and all
is only done as a display function
comparison and not systems evaluation,
processing systems; each is slightly
There is not sufficient information in
to make them the sole basis for choosing
authors have deliberately avoided making
The selection of a system will have
as operating speed (especially for the
multispectral classification, if that is a prime use of the equipment),
the flexibility with which other operations are possible, the ease of
communication with the system during operations, the ease of writing and
implementing new functions, and the cost of the system.
Finally, the tables have been designed for use by analysts with some degree
of familiarity with image processing. They cannot serve as a training
course in image processing. The reader desiring additional information*
is encouraged to refer to the extensive literature on the subject. For
clarification, some terms used herein are defined following the tables.
The tables and the System Summaries have been prepared primarily from
information supplied by the manufacturers. While some rewording has been
done to make the descriptions parallel, the manufacturers' wording has
been retained to a large extent.
SYSTEM SUMMARIES
G.E. IMAGE-100
An interactive image analysis system designed for multispectral classification
of satellite and aircraft multispectral scanner data, with limited general-
purpose processing available. The hardware system includes a PDPll-class
computer, an interactive image analysis console containing a hardware
classifier and other specialized processing functions, five channels of
memory for image processing and display refresh with thematic overlay capa
bility, and a color display.
Sold as a complete system with proprietary software. Can be expanded and(or)
reconfigured to meet specialized user requirements.
General Electric CompanySpace DivisionP.O. Box 2500Daytona Beach, Florida 32015(904) 258-2924Contact: Robert W. Towles
Manager, Image Processing Applications
BENDIX MDAS
A combination hardware-software system designed primarily for multispectral
classification of satellite and aircraft multispectral scanner data, with
limited general purpose software processing available. The hardware system
includes a PDP-11 and an interactive image analysis console containing a
hardware classifier and some specialized processing functions. The system
can process up to 16 channels of image data simultaneously and has a solid-
state refreshed 3-color display with graphic overlay.
Sold as a complete system with proprietary software. Can be expanded to
meet user requirements.
The Bendix CorporationAerospace Systems Division3621 S. State RoadAnn Arbor, Michigan 48107(313) 665-7766Contact: Mr. Charles L. Wilson
Manager, Earth Resources Applications
I 2S SYSTEM 101
An interactive multi-user digital image processing system including multi-
spectral analysis and an expandable set of general purpose algorithms. The
hardware consists of a Hewlett-Packard 3000 Series II Computer with disc
image storage and user console containing up to 14 channels of refresh
memory, with hardware processing at video rate, a programmable floating
point image array processor and color displays.
Sold as a specific complete system with proprietary software, configured
to user requirements.
International Imaging Systems Division of Stanford Technology Corporation 650 North Mary Avenue Sunnyvale, California 94086 (408) 737-0200Contact: Mr. Paul Papathakis
Director of Marketing
ESL IDIMS
A combination hardware-software system for general purpose interactive,
multi-user image processing including multispectral analysis and classifi
cation. Hardware includes: Hewlett-Packard 3000 Series 11 computer,
interactive processing console including a programmable array processor,
3 or more channels of refresh memory with video color display; refresh
memory is CCD or random access. Software can also process collateral data.
Sold as a complete system with proprietary software with configuration
tailored to user needs.
Electromagnetic Systems Laboratories, Inc.495 Java DriveSunnyvale, California 94086(408) 734-2244Contact: Dr. James E. Burke
Manager, Image Data Systems
COMTAL SERIES 9
A complete stand-alone system designed for both multispectral data classifi
cation and general purpose image analysis and enhancement of up to four
separate image planes simultaneously. It incorporates a combination of
hardware and software functions to provide maximum processing speed and
capability while maintaining complete functional flexibility. Changes in
algorithms and processing techniques may be implemented by software changes.
Major subsystems are magnetic tapes, computer, and 8000 Series display.
Comtal Corporation169 North Hal steadPasadena, California 91107(213) 793-2134Contact: Dr. John Tahl, President
ISI SYSTEM 470 AND SAND
Combination hardware-software systems for general purpose image processing
and multispectral analysis. Swing (proprietary) software and digital computer
and peripherals are the same in both; 470 contains real-time video processing
and 600 image video disc store; SAND is RAM (Random Access Memory)-based for
interactive computer graphics applications.
Specific configurations may be tailored to user needs.
Interpretation Systems IncorporatedP.O. Box 1007Lawrence, Kansas 66044(913) 842-5678Contact: Mr. Jerry D. Lent
Director, International Marketing
KANDIDATS
KANDIDATS is a digital image processing system that interacts with the usere=
at the command string level. It includes prompting for parameter input and
checks user input for errors. Image analysis programs available in KANDIDATS
consist of utility functions, image transform operations, spatial clustering,
and Bayesian classification. Programming structure and file structure are
modular.
Dr. Robert Haralick Space Technology Center University of Kansas Lawrence, Kansas 66045 (913) 864-3542
JPL VICAR
A Fortran-based expandable general purpose image processing software system.
It includes a wide variety of general purpose algorithms including multi-
spectral analysis and computation. Implemented at JPL initially on IBM-360/
44; recently modified to 360/65. Computer peripherals serviced by the
system include: 2 Comtal interactive consoles, a Ramtek refresh memory, a
quick look Polaroid hardcopy output, and off-line film recording.
Software system available from COSMIC includes documentation and listings.
Jet Propulsion Laboratory 4800 Oak Grove Drive Pasadena, California 91103 (213) 354-5016 Contact: Mr. William B. Green
Section Manager, Science Data Analysis Section
PURDUE LARSYS
Combination hardware-software image processing facility at the Laboratory
for Applications of Remote Sensing (LARS) in West Lafayette, Indiana.
System is used locally and also supports remote terminals via phone line.
The software system (LARSYS) is primarily designed for multispectral
classification, but also includes limited general purpose image processing.
Hardware is an IBM-360/67 plus an interactive console containing a black-
and-white video display with facilities for black-and-white and color
photographic output.
System hardware is not for sale, but several terminals are available
throughout the country and at West Lafayette. System software is available
through COSMIC.
Purdue UniversityLaboratory for Applications of Remote Sensing (LARS)Purdue Industrial Research Park1220 Potter DriveWest Lafayette, Indiana 47906(317) 749-2052Contact: Mr. Terry L. Phillips
Deputy Director, System Services
8
TABLE
1GE
NERA
L PURPOSE
IMAG
E PROCESSING
Page
1
of
3
RADIOMETRIC
FUNCTION
GE IM
AGE
100
BENDIX M
DAS
I2S
SYST
EM 10*1
RADI
OMET
RIC
CORR
ECTI
ONLandsat
deba
ndin
g, correction
for
6-se
nsor
unb
alan
ce o
f MSS
Corr
ecti
on o
f photographic d
ata
Othe
r
Line
by
line
ga
in a
nd o
ffset
(Opt
iona
l so
ftwa
re,
or so
ft
ware
/har
dwar
e hy
brid
)Average
adja
cent
li
nes
NoAv
erag
e adjacent li
nes
Hard
ware
shading
(for
TV
camera in
put)
Shad
ing,
when u
sing
vidicon
option
D-log
E correction
Shad
ing
Focu
s correction
Motion d
e-bl
urri
ng
Video
averaging
soft
ware
To
r no
ise
remo
val
Atmo
sphe
ric
correction
by
regression analysis
Sun
angl
e co
rrec
tion
DIGI
TAL
LEVE
L SL
ICIN
GContinuum
B/W
to m
ultiple
disc
rete
grey shades
Assignment of colors
to
disc
rete
grey shades
8-le
vel
(to
them
e tr
acks
) N-
leve
l (O
ptio
nal)
co
mple
tely
flexible spacing
* 2-
1-le
vel:
Of
fset
, counts/level
0 offset,
gain
(8 levels/band,
equal
size)
A N-lcvcl
with fl
exib
le spacing
by card input
N-level
Comp
lete
ly fl
exib
le spacing
Line
ar,
high and
low
limi
t,
0 of st
eps
64 p
reset
colo
rs,
8 at
a time
N-level
- arbitrary
color
assi
gnme
nts
* 24 preset colors
0 Ar
bitr
ary
colo
r as
signme
nt,
A 51
2 co
lors
available
(false
color
mode)
Arbitrary
colo
r assignment,
512
colors available
Single level
color
slice
on
B/W
image
CONT
RAST S
TRET
CHTa
ble
look
up implementation
Line
al-
Equa
l occupancy
Square r
oot
Piecewise
line
ar (O
pt.)
Table
look
up im
plem
entati
on
Equal
occupancy
Square r
oot
Piecewise
line
ar (O
pt.)
Variable ga
in a
nd o
ffset
(pla
nned
)
Linear
Equa
l oc
cupa
ncy
Logarithmic
Piecewise
line
arExponential
TABL
I;
1Gi'.NLRAL PURPOSE IM
AGE
PROCESSING
Page
1 of
3
(Continued)
RADI
OMET
RIC
FUNCTION
SI, HUMS
COMT
AI,
STHI
IiS
ISll SYSTKM 4?0 ,
SAND
RADIOMFTRIC CORRECTION
Lundsat
dcbn
ndin
g, correction
for
6-se
nsor
unbalance of
MSS
Corr
ecti
on o
f ph
otog
raph
ic d
ata
Other
Average
adja
cent
li
nos
Notc
hed
filt
erin
gNo
Shading
correction
Focus
correction
Motion d
e-bl
urri
ng
No
Atmospheric
corr
ecti
ons
(planned)
Sun
angle
corr
ecti
on
Replace
adja
cent
line
Average
adja
cent
lines
Shad
ing
correction
Focu
s co
rrec
tion
(planned)
DIGI
TAL
LEVEL
SLICING
Cont
inuum
B/W
to m
ulti
ple
discrete g
rey
shades
Assi
gnme
nt o
f co
lors
to
discrete g
rey
shades
N-le
vel
Comp
lete
ly f
lexible
spac
ing
N-le
vel
Arbitrary
color
assi
gnme
nt,
4096
col
ors
avai
labl
e, 64
at
a
time
fo
r display
Colo
r contouring
8-le
vel
(har
dwar
e re
al-t
ime)
N-
leve
l software
Comp
lete
ly f
lexi
ble
spac
ing
Arbitrary
level
setting
(color c
ontouring
- SAND)
CONT
RAST
STRETCH
15 m
ajor types
of i
nten
sity
transformations.
Variety of
int
erac
tive
tra
nsfo
rms
Table
look
-up
Line
ar
Loga
rith
mic
Piec
ewis
e linear
TARL
C 1
GP.NF.RAL
PURP
OS1-
TMACli PROCF.SS1NG
(SOFTWARE
SY5T
F.MS
\of
3
(Con
tinu
ed-)
RADI
OMET
RIC
FUNCTION
RADI
OMET
RIC
CORRECTION
Landsat
dchanding, co
rrec
tion
for
6-sensor u
nbal
ance
of MSS
Correction o
f ph
otog
raph
ic d
ata
Othe
r
KAND
TDAT
S
Aver
age
adja
cent
li
nes
No Point
corr
ecti
on
JIM,
VIC
AR
*Average adjacent li
nes
Convolution
filt
erin
g Li
ne by li
ne ga
in and
offs
et
Four
ier
fiIt
erin
g
Shad
ing
P-log
E correction
Focu
s co
rrec
tion
Aver
age
several
images for
noise
correction
Individual pi
xel
corr
ecti
on
LARS
YS
Gain
an
d of
fset
*Avi
M*ag
c adjacent li
nes
*Fou
ricr
filtering
*Sca
nncr
an
gle
correction
*Convolutional
t'i Itering
*Sha
d in
g
*Focus correction
*Fin
itc
aperture co
rrec
tion
DIGI
TAL
LEVE
L SL
ICIN
GCo
ntinuum
B/W
to m
ulti
ple
discrete gr
ey sh
ades
Assi
gnme
nt of
colors
to
disc
rete g
rey
shad
es
N-level, flexible
Grey
sca
le li
ne p
rint
erN-
leve
l flexible tabl
e Li
near
-arb
itra
ry endpoints
Log
Exponential
Grey
scale
line
printer
N-le
vel
flexible table
Grey scale
line p
rinter
Arbitrary, in
dis
play
memory,
10-c
olor
*Arbitrary (a
naly
st-g
ener
ated
ta
bles
in color
space)
*Arb
itra
ry (a
naly
st-g
ener
ated
color
tabl
es)
CONT
RAST STR
ETCH
* No
t in
COSMIC
Linear
Equa
l occupancy
General
non-linear
Tabl
e lo
okup
im
plem
entation
Linear,
arbi
trar
y en
d points
F.qu
al occupancy
Contouring
Flex
ible
table
Logarithmic
Expo
nent
ial
Piec
ewis
e li
near
Flexible table
lookup
Equa
l oc
cupa
ncy
TAIW
, 1
Miur
osi;
IMAM
I'UO
CP.SS
INC,
Page
2
of
3
GEOM
ETRI
C CO
RREC
TION
5
REG.
ISTR
ATIO
N!r,n
IMA
GE 1
00BHNDIX M
DAS
I2S SY
STEM
10
1
CORR
ECTI
ONS
Inte
rnal
sensor d
isto
rtio
nsMirror scan ve
loci
ty p
rofile
(Opt,)
Roll
, pi
tch,
ya
w (Opt,)
Ephe
meri
s (altitude
and
velo
city
) (Opt.)
Skew
As
pect
ratio
and
scaling
Std.
: By line selection
Opt,:
By interpolation
Mirror scan velocity p
rofile
Rol
\j pitch, ya
wEp
heme
ris
(altitude
and
velocity)
Skew
Aspect ratio
by ne
ares
t neigh
bor
Scal
ing
Mirror scan v
eloc
ity
prof
ile
Roll,
pitch, ya
w
Skew
Aspect ra
tio
Scaling
- re
move
sy
nthe
tic
pixels
External - projective ge
omet
ry
distortions
Map
Projections:
Spac
e ob
liqu
e Me
rcat
or (Opt,)
Map
Proj
ecti
ons:
UTM
Lat/
Long
State
plane
Map
Projections:
UTM
Spac
e ob
liqu
e Me
rcat
or
Albe
rs equal
area
Polar
stcrcographic
State
plan
e Lambert
conformal
North
American p
olyconic
Flexible rubber sheet
stre
tch
in
g (A
rray
pr
oces
sor
planned)
Image
rota
tion
(A
rray
processor
plan
ned)
Perspective
correction
REGI
STRATI
ONDe
velo
pmen
t of reg
istr
atio
n parameters
Mapp
ing
of g
round
control
poin
ts
to entire sc
ene
or subscene
Digital
temporal and ma
ppin
g ov
erla
yImage
to image
Image
to map
Cursor de
sign
ates
li
ne and
pixel
of se
lect
ed fe
atur
esInteractive
sele
ctio
n of c
on
trol
points (I
nclu
des
dis
played GCP's
from m
aps)
One
pixe
l dot
for
GCP
location
(blinking)
Interactive
sele
ctio
n of c
on
trol
points from su
bsce
nes,
merged for
full sc
ene
cor
rection
(Up
to 100
GCP
max.)
Leas
t squares
fit
to a ma
ximu
mof
16 GCP's
(Opt.)
Tran
slat
ion
only
with
stan
dard
soft
ware
Least
squares
fit
to a
maximum
of 9
9 GC
P's
Computed surface
fit
by nth
orde
r polynomial
Subs
cene
only (Opt.)
Full
sc
ene
(Opt.)
Full
sc
ene
Full
scene
Vari
able
scales (Opt.)
Variable scales
Vari
able
scales
TABLfi
1RF.NI-RAI. PU
RPOS
E 1M
ACK
PROC
ESS IN
KPa
ge J_ of _3
(Con
tinu
ed)
GEOMETRIC
CORRECTION 6
REGISTRATION
ESL
IDIM
SCOMTAL SE
RIES
9
ISI
SYST
EM 470, SAND
CORR
ECTI
ONS
NoIntern
al sensor dis
tort
ion
(Lan
dsat
MSS)
Skew
Aspect r
atio
to
79x79
meter IF
OSc
alin
g fo
r li
ne p
rinter to
sp
ecif
ied
scale
Mirror sc
an v
eloc
ity
prof
ile,
ro
ll,
pitc
h, ya
w, de
tect
or
sampling d
elay
(planned).
Mirror scan v
eloc
ity
prof
ile
Roll
, pi
tch,
yaw
Skew
External - pr
otec
tive
geometry
dist
ortions
NoIm
age
rotation
Map
proj
ecti
on (p
lann
ed)
Rubber sh
eet
stretching
Imag
e ro
tati
onRound
earth
Flexible r
ubber
sheet
REGISTRATION
Development
of reg
istr
atio
n pa
ramete
rs
Mappin
g of g
round
cont
rol
points
to e
ntire
scen
e or s
ubsc
ene
Digital
temp
oral
an
d ma
ppin
g overlay
Image
to im
age
Image
to m
ap
Inte
ract
ive
cursor s
election o
f co
ntro
l points
Interactive
cursor location o
f co
ntro
l points
Manu
al se
lect
ions
of p
oint
s by
coordinates
Curs
or selection
of G
CPs
Least
squa
res
fit
to p
oly
nomials
(up to c
ubic
)Le
ast
squa
res
fit
per
512x
512
sub-image
Full
scene
Yes
Entire im
age
by m
osai
c of
sub-
imag
es
Variable sc
ales
Vari
able
scales
TABlJ:
1.C.F.NF.RAI, Pl
IKPO
SI-
IMACI
: PUOCIiSSINC. (SOFTWARE
SYSTEMS)
Pago
1 of
(Continued)
GEOMGTRIC
CORR
ECTI
ON 5 RE
GIST
RATI
ON
CORRECTIONS
Internal sensor d
istortions
(Lands
at MS
S)
External - projective geometry
distorti
ons
KANDtDATS
Skew
Scal
e by
nearest ne
ighb
orVe
rtic
al skew al
so available
-JPL
VIC
AR
'Mir
ror
scan
velocity pr
ofil
e*R
oll,
pitch, yaw
*Skcw
Aspect ratio
Scal
ing
- by interpolation
Flexible rubber sheet
byfunction
Rotation,
translation, skew,
scale
by m
atri
x co
effi
cien
ts
Space ob
liqu
e Me
rcat
or
Imag
e ro
tati
on P
roje
ctio
n to st
anda
rd map
Flex
ible
rubber sh
eet
stretch
ing
LARSYS
"Ske
wAspect ra
tio
Scal
ing
Image ro
tati
on Rubber
shee
t stretching
REGI
STRATI
ONDe
velo
pmen
t of reg
istr
atio
n pa
rame
ters
Mapping
of g
round
control
points to entire scene
or
subscene
Digital
temporal an
d ma
ppin
g ov
erla
yImage
to image
Imag
e to
ma
p
Not
in COSMIC
Manual co
ntro
l points
Man
ual
or interactive
sele
ctio
n of c
ontrol points
Cross correlation
of a
reas
around selected control
poin
ts
Man
ual
selection
of control
points
Computed
bloc
k co
rrel
atio
ns
for
12-30
blocks per
scene
2x2
tran
sfor
mati
on ma
trix
Tria
ngul
ar facet
surf
ace
fit
'Biq
uadr
atic
fit
to G
CP's
Partial
scen
e, limited
by
computer si
zeFu
llor
partial
scen
e*Full
scene
By control
poin
tVa
riab
le scales
"Yes
TABL
E 1
GENERAL
PURPOSE
IMAG
E PROCESSING
Page
of
OTHE
R SY
STEM
FUNCTIONS
GE IMAGE
100
BENDIX MDA
SI2
,S S
YSTE
M 10
1
GEOM
ETRI
C INTERPOLATION
TECHNIQU
ESNearest
neig
hbor
(O
pt,)
Cubic
conv
olut
ion
(Opt
.)Bi
line
ar (O
pt.)
Lagr
angi
an (O
pt,)
Hard
ware
/sof
twar
e im
plem
enta
ti
on a
llows
any
4x4
tech
niqu
e to
be
used
Nearest
neig
hbor
Soft
ware
implementatipn
of
any
4x8
technique
incl
udin
g re
stor
atio
n, cu
bic
convolu
tion,
bilinear Lagrangian
(Opt
.)
Nearest
neig
hbor
Bilinear
Cubi
c co
nvol
utio
n (p
lann
ed)
FILT
ERING
High
pas
s, lo
w pa
ss,
Lapl
acia
n(O
pt,)
Th
eme
filtering via
Go lay
surrounds
(Opt
,.)
Sin
x/x
filter s
oftware
for
window d
isplay
(Standard),
hard
ware
fo
r fu
llsc
reen
(O
pt.)
"Restoration"
(Bcndix pr
opri
e
tary t
echn
ique
)Any
line
ar fi
lter
(Sin
x/x,
high
pass, lo
w pass,
Laplacian)
Convolution;
Gaus
sian
High p
ass
Low
pass
Wiener
Homo
morp
hic
Dire
ctio
nal
Fourier
transform
Hada
mard
transform
TRANSFORMS
Four
ier
Hada
mard
Othe
r
NoYe
sYe
s (h
ardw
are
and
software)
Yes
(hardware/software
Yes
Yes
(har
dwar
e an
d software)
Categorical
tran
sfor
mSlant
TABLE
1GENERAL
PURP
OSE
IMAGE
PROC
ESSI
NG, P
age
3 of
3
(Continued)
OTHE
R SY
STEM
FUNCTIONS
ESL
ID1M
SCO
MTAL
SERIES
9ISI
SYST
EM 4
70, «A
ND
GEOM
ETRI
C INTERPOLATION
TECHNIQUES
Nearest
neig
hbor
Bili
near
Cubi
c co
nvol
utio
n
Near
est
neig
hbor
Bi
line
arNe
ares
t ne
ighb
orBi
line
arCu
bic
conv
olut
ion
FILTERING
Convolution
- using
arbi
trar
y kernal
Wien
erHo
momo
rphi
c -
Dire
ctio
nal
Ten
different
rout
ines
for
filter g
ener
atio
n Fo
urie
r tr
ansf
orm
NoConvolution
~ us
ing
arbitrary
kernal
LaPlacian
Robert's gr
adie
nt
Theme
filt
erin
g by Grow/Shrink
and
generalized
temp
late
mat
ch
TRAN
SFOR
MSFourier
Hadamard
Other
Yes
No
Yes
No
Yes
Yes
Discreet c
osin
e Discreet L
inea
r Ba
sis
Slan
t
TABLE
1GE
NERA
L PU
RPOS
E IM
AGE
PROC
ESSI
NG (SOFTWARE
SYSTEMS)
Page
3 of
3
(Continued)
OTHER SY
STEM
FUNCTIONS
KANDIDATS
JPL VI
CAR
LARSYS
GEOMETRIC
INTERPOLATION
TECHNIQUES
Near
est
neighbor
Near
est
neig
hbor
Bi
line
ar*Cubic convolution
*Spline
*Sin
x/x
'Nearest ne
ighb
or*Cubic
*Spline
*Sin
x/
x
FILTER
ING
Them
e cl
eanu
p by
grow-shrink
Rectangular
box
filter
3x3
medi
an filtqr
Grad
ient
, Ge
nera
lize
dLaplacian
3x3
linear filter
Wien
erCo
nvol
utio
n - fu
ncti
on se
lect
ed
by p
arameter in
put
(eg.
low
pass,
high p
ass,
Lapl
acia
n, directional)
Fourier
tran
sfor
m
*Convolution
*0ptimum constrained
rest
orat
ion
*Laplacian
'Gra
dien
t*F
ouri
cr transform
TRAN
SFOR
MSFo
urie
r
Hadamard
Other
*Not
in COS
MIC
Yes
Yes
'Yes
Yes
'Yes
'Yes
Slant
Discrete c
osin
eDiscrete linear b
asis
*Various co
lor
space
tran
sfor
ms
TABLE
2MULTISPECTRAL
CLASSIFICATION
Page
1 of
2
MULT
ISPECT
RAL
CLASSIFICATION
GE IMAGE
100
BENDIX M
DAS
I2S SY
STEM
1Q
1
SUPE
RVIS
ED C
LASS
IFIE
RParallelepiped (s
ingl
e-ce
ll)
Table
look
up (m
ulti
-cel
l)
Nonparajmetric j
naxi
mum
like
li
hood (O
pt.)
Ha
rdwa
re/s
oftw
are
implementa^
tion
Hard
ware
bul
k classifier,
in*
elud
ing
table
look
up an
d pa
rame
tric
max
imum
li
keli
hood
(O
pt,)
Bayesian maximum li
keliho
od
Gaussian or
aggregate
Gaus
sian
standard
Maxi
mum
likelihood
Parallelepiped
Table
look
up (h
ardw
are
and
software)
UNSU
PERVISED
CLASSIFIER
Spec
tral space
clus
teri
ng
Region
gro
wing
in
image
space
Semi
-sup
ervi
sed
software(Opt,)
Yes
(Opt
,)Yes
- software - ca
n be
done
on c
urso
r-de
sign
ated
polygon
MENS
URATION
Pixe
l count
of s
trat
aFu
ll screen
Suba
reas
by
them
atic
mask
I'ot
al scene
Cursor e
nclo
sed
area
Interactive
manual d
igit
izer
Mu
ltip
le scene
areas
Subsccnc d
efined b
y cursor o
r re
ctan
gula
r wi
ndow
INTE
R-BA
ND MAN
IPUL
ATIO
NIn
ter-band functions
Spec
tral an
alys
is
Spec
tral Ax
is Rotations
Rati
oing
, di
ffer
ence
-ove
r-su
m,
norm
aliz
atio
n (hardware)
Rati
oing
(software)
+ - x
T (hardware
and
soft
ware
)
Eigenvector
(software)
Eigenvector
Regr
essi
onFactor
Eige
nvec
tor
(har
dwar
e and
software)
Karh
unen
-Loe
ve (h
ardw
are/
so
ftwa
re)
General
Axis R
otat
ion
(hard
ware)
Karh
unen
-Loe
ve
General
Axis Ro
tati
onKa
rhun
en-L
oeve
(h
ardw
are
and
soft
ware
) General
Axis R
otation
TABLE
2MU
LTIS
PECT
RAL
CLAS
SIFI
CATI
ON (SOFTWARE
SYSTEMS)
Page
1 of
2 (C
onti
nued
)
MULT
ISPE
CTRA
L CL
ASSI
FICA
TION
KANDIDATS
JPL VI
CAR
LARSYS
»'
SUPERVISED CLA
SSIF
IER
Bayesian ta
ble
lookup wi
th
spatial
neig
hbor
bac
kup
*Bay
esia
n*Parallelcpiped
tabl
e lookup
'Par
alle
lepi
ped
table
lookup
with
Ba
yesi
an se
cond
ary
clas
sifi
er*Stored
table
Bayesian
Maxi
mum
like
liho
od for
each
pixe
lSample (p
er fi
eld)
cl
assi
fier
*Multiimage
layered
classifier
UNSU
PERV
ISED
CLASSIFIER
Spec
tral
sp
ace
clus
teri
ng
Regi
on gr
owin
g in image
spac
e
Euclidian distance in
me
asur
emen
t space
Not
at pr
esen
tYe
s
Boun
dari
es by
Roberts
grad
ient
and
adap
tive
th
resh
oldi
ng
*Aut
omat
ic bou
ndar
y fi
ndin
g/sa
mple
cl
assi
fica
tion
MENSURAT
ION
Yes
r subareas by b
inary
mask
Yes
INTER-BAND MAN
IPUL
ATIO
NIn
ter-
band
functions
Spectral analysis
Spectral axis rotations
'Not in
CO
SMIC
Algebraic
operations
+ - x
T av
erag
ing
Any
Fort
ran-
writ
able
fu
ncti
onRatioing
Eigenvector, by
tra
inin
g ar
eas
or on
al
l data
^Eigenvector
*Eig
enve
ctor
Karhunen-Loeve.
Also
fa
st K-L
General
Axis
Ro
tati
ons
*Karhunen-Loeve
General
Axis Rotations
*Karhunen-Loeve
TABLE
2MULTISPECTRAL
CLAS
SIFI
CATI
ONPa
Seof __2
(Continued)
MULT
ISPE
CTRA
L CL
ASSI
FICA
TION
ESL
IDIM
SCO
MTAL
SERIES
9I S
I' SYS
TEM
478*
, SA
ND
SUPE
RVIS
ED C
LASSIFIER
Adva
nced
stored ta
ble
(Bayesian)
Maximum
likelihood (a
rray
proc
esso
r)
Minimum
dist
ance
(Euclidian)
Para
llel
pipc
dParallelpiped
Bayesian
Table
look-up
Non-
para
metr
ic(h
ardw
are/
soft
ware
im
plem
enta
tion -
SAND
)
UNSU
PERV
ISED
CLA
SSIF
IER
Spectral sp
ace
clustering
Region
gr
owin
g in imago
spac
e
ISOCLS (iterative)
clas
sifi
er
T. can
be d
one
on cursor-
desi
gnat
ed su
b-ar
ea
No
Iterative
spatial
clus
teri
ng
based
on homogeneous
regions,
edge detection
and
enhancement
and
thre
shol
ding
MENSURATION
Yes
- by
st
i'at
a bi
nary
mus
k,
curs
or-d
esig
nate
d ar
ea,
or
inte
ract
ive
manual di
giti
zer.
Stereo m
ensu
rati
on (opt,)
Yes
- hardware 1/
30 sec,
Total
scene
or arbitrary
sub-
ar
ea (optional
real-time
mensuration
hardware)
INTER-BAND MAN
IPUL
ATIO
NIn
ter-
band
fu
ncti
ons
Spec
tral
an
alys
is
Spec
tral
axis ro
tati
ons
Sum, Difference,
Prod
uct,
Ra
tio
Sum, Difference,
Prod
uct,
Ra
tio
and
comb
ined
fu
ncti
ons
Ratio
Array
and
scal
ar a
rithmetic
Logical
operations
Algebraic
func
tion
s
Eige
nvec
tor
Eige
nvec
tor
Eige
nvec
tor
Karh
unen
-Loe
ve
General
axis ro
tati
onKa
rhun
en-L
oeve
General
axis
ro
tati
on
TABLE
2MU
LTIS
PECT
RAL
ANAL
YSIS
Page
2 of
2
MULTISPECTRAL AN
ALYS
ISGE IM
AGE
100
BF.NDIX MD
ASSY
STEM
*01
STAT
ISTI
CAL
OPERATIONS
Training f
ield selection
Deri
vati
on o
f training f
ield
statistics
Maximum number o
f sp
ectr
al
bands
anal
yzed
si
mult
aneo
usly
Maximum number o
f cl
asse
s
Optimum band s
elec
tion
Clas
sifi
cati
on s
peed
(p
er
512x51
2 pixel
4-band sc
ene)
Single p
ixel (c
ross
-hai
r),
rectangle, 45°
rotated
rect
angl
ePolygon
cursor (O
pt.)
Any
shap
e qu
adri
late
ral
as
small
as
1 pixel
with a
ny
orie
ntat
ion
Full scene
Any
shape
desi
gnat
edIn
tera
ctiv
e selection
Cova
rian
ce m
atri
ces
Hist
ogra
msHardware/software
impl
emen
ta
tion
Time in
depe
nden
t of s
ize
Covariance m
atri
ces
Histograms (O
pt,)
Covariance m
atri
ces
4; 5 wi
th r
atio
ing
Up t
o 16
(O
pt.)
1614 - Di
spla
y processor
or 36 - Central
proc
esso
r
Any
numb
er,
8 themes d
isplayable
at o
ne t
ime superimposed o
n'
vide
o.
50,
disp
lay
hand
les
any number
simu
ltan
eous
ly64
Opti
onal
in
tera
ctiv
e feature
selection
software -
<4 o
ut o
f 16
max
.
All
input da
ta c
hannels
pro
cessed u
nless
oper
ator o
ver
ridden
Rati
os an
d di
verg
ence
analysis
Nomi
nall
y 3-
5 seconds per
class
(multicell signature)
CCT-
limi
ted
(I/O
li
mit)
20 m
in.
tota
l \
scen
e
10 c
lass
-
2 min. wi
th a
rray
processor
(lin
ear
with n
umbe
r of
classes)
TABL
b 2
MUL1
ISPE
CTRA
L ANALYSIS
Page
2 of
2
(Continued)
MULTISPECTRAL
ANAL
YSIS
ESL
IDIM
SCO
MTAL
SERIES 9
,.ISI SYSTEM-470,
SAND
STATIS
TICA
L OPERATIONS
Trai
ning
field
sele
ctio
nInteractive
selection
of
polygonal
areas
with
cursor
(21
subcommands)
Random sampling
Any
shap
e quadrilateral
up to
8 active
Derivation of
tra
inin
g fi
eld
statistics
Cova
rian
ce m
atri
ces
Stat
isti
cs file editor
Covariance m
atrices
Maxi
mum nu
mber
of
spec
tral
ban
ds
anal
yzed
si
mult
aneo
usly
Maxi
mum nu
mber
of cl
asse
s
Opti
mum ba
nd se
lect
ion
Clas
sifi
cati
on s
peed
(p
er
512x
512 pi
xel
4-ba
nd scene)
255
256
in one
pass
Yes
Manu
al
10 c
lass
-
52 se
c. wi
th A
SAP
(lin
ear with num
ber
of c
lasses)
Interactive
sele
ctio
n via
curs
or o
r ma
nual
sp
ecif
ica
tion by
poly
gon
vert
ices
Designated b
y arbitrary
irre
gula
r boundary
Hist
ogra
ms
Cova
rian
ce m
atri
ces
(Har
dwar
e/so
ftwa
re implementa
tion -
SAND)
14 256 wi
th speed
pena
lty
255
in one
pass
(8 pe
r pass at m
aximum sp
eed)
Non-
para
metr
ic
Bhattacharyya
470
- Ba
yes,
up
to 16
cl
asse
s,
disc
I/
O li
mit,
<20
sees
. SAND -
from m
emory, <2.5 sees.
TABL
E 2
MULT
ISPE
CTRA
L AN
ALYS
IS(SOFTWARE
SYST
EMS)
Pa&e
2
of
2 (Continued)
MULTISPECTRAL ANALYSIS
KANDIDATS
JPL
VICA
Ri'
LARSYS
STATISTICAL OP
ERAT
IONS
Trai
ning
field
selection
Manual on
di
spla
y re
ctan
gula
r area
Any
shap
e de
sign
ated
*P
olyg
on v
ertices
(may b
e fr
om
maps)
Rect
angl
e by
li
ne an
d column
Deri
vati
on o
f training field
stat
isti
csSm
ooth
ed Ga
ussi
an
Mean
an
d co
vari
ance
mat
rix
by c
lass
*Covariance
matrices or
manual
para
llel
epip
ed limits
Cova
rian
ce matrices fr
om
training fi
eld
or c
lust
erin
g re
sult
s
Maxi
mum nu
mber
of
spectral
bands
analyzed si
mult
aneo
usly
Maxi
mum nu
mber
of
clas
ses
Opti
mum ba
nd selection
Clas
sifi
cati
on sp
eed
(per
51
2x51
2 pixel
4-band sc
ene)
(Very
mach
ine-
depe
nden
t.
Included a
s illustrative only.]
* Not
in C
OSMI
C
Depe
nds
on mem
ory
avai
labl
e an
d length of
line
1630
1850
60
Operator selection
Bhattacharyya co
effi
cien
ts*Yes,
including ra
tios
Yes
- transformed
dive
rgen
ce
(ave
rage
over class
pairs,
maximized
minimum
pair
wisc
)
10 c
lass
es - CPU
time 45
seco
nds
- pa
rall
elepip
ed only
Appr
ox.
1.5
minu
tes
- paral
lelepiped
with 2
clas
s Ba
yesi
an re
solu
tion
- al
l pixels 12 m
inutes - parallel
epiped wi
th 10
class Bayesian
resolution -
all
pixels
TABLE
3SYSTEM IN
PUTS
Page
1
of
1
INPUT
DEVICE
GE IMAGE
100
BENDIX MDA
SI?
S SY
STEM
161
TV CAMERA
or e
quiv
alen
t (ima
gery)
Yes,
silicon
vidi
con
Opti
onal
vid
icon
Yes, vi
dico
n
MICR
ODENSITOMETER
Drum s
cann
er
Other
Optr
onic
s (O
pt.)
Optronics
(Opt,)
Optr
onic
s
Perk
in-E
lmer
10
10A
can
be
used w
ith
system
DIGITA
L TAPES
NASA
Landsat
Skylab S
I92
(Opt
.)LARSYS (O
pt.)
INPE
Landsat (O
pt.)
Airc
raft
scanner
(Opt
.)CCRS Landsat
(Opt
.)JSC
Universal
(Opt
.)HD
DT t
o CCT
conversion for
aircraft scanners (
unde
rconstruction)
Land
sat
Bcnd
ix M
^S scanner
$Sk
ylab
S1
92
$IN
PE (Brazil)
MSDS
(24
channel
scanner) $
BRIM s
canner
$
$ (C
CT a
nd H
DDT)
Landsat
ANAL
OG TAP
ESFM tap
e to
CCT c
onverter
for
Daedalus a
nalog
scan
ner
(developed a
nd o
perating)
(Opt
,
Opti
onal
No
TABL
E 3
SYST
EM INPUTS
Page
1 of
1
(Continued)
INPU
T DEVICE
ESL
IDIM
SCOMTAL SKRIHS 9
ISI
SYST
EM 4
70,
SAND
TV CAM
ERA
or eq
uiva
lent
(i
mage
ry)
Not
at ESL
facility
(sys
tem
opti
on)
Spec
ial
system op
tion
Yes,
vi
dico
n
MICRODENSITOMETER
Drum sc
anne
r
Other
Opti
onal
- us
er c
hoice
No
Pcrk
in-E
lmer
1010A
No
Opti
onal
(h
igh
spee
d 8-bit
video
digitizer
is included
as st
anda
rd co
mpon
ent)
No
DIGI
TAL TA
PES
Land
sat
Skylab S
192
Airc
raft
scanner
PCM
Land
sat
VICAR
Landsat
JSC
Universal
Skylab S
192
Swin
g (ISI software s
td.)
ANAL
OG TAPES
FM a
t ES
L facility
NoNo
TABL
E 3
SYST
EM INPUTS (S
OFTW
ARE
SYST
EMS)
Page
1 of
1 (Continued)
INPU
T DEVICE
TV C
AMERA or e
quivalent
(ima
gery
)
MICRODENSITOMETER
Drum sc
anne
r
Othe
r
DIGITAL TAPE
S
ANAL
OG TAPES
* Not
in CO
SMIC
KANDIDATS
Land sat
Skyl
ab S192
LARSYS
JSC
Universal
No
JPL
VICA
R
Inte
rfac
e software fo
r;
CRT
scanner
*Dic
omcd
im
age
diss
ecto
r sc
anne
r
Inte
rfac
e software fo
r:
I'erkin El
mer
1010
* Land sa
t *Skylab
S192
*Bcndix M2S
*NAS
A 24 channel
VICA
R
No
,,
LARS
YS.
«
*Int
erfa
ce so
ftwa
re
*0ptronics
LARSYS
* Lan
d sa
t *A
ircr
aft
scanner
*Sky
lab
S192
*CCU
S *JSC u
niversal
*VICAR
*Yes
TABLE
SYSTEM OUTPUTS
Page
1 of
2
OUTPUT
GE IM
AGE
100
BUND
IX M
DAS
1,2S
SYSTEM \p
l
VOLA
TILE
DISPLAY
Graphics
Two-
dimensional
grap
hic
disp
lay
CRT di
spla
y - grey s
cale o
r color
imag
e
Anno
tati
on
Tektronix
Yes
Yes
Cova
rian
ce m
atri
x Cl
uste
r pl
otti
ng
Hist
ogra
ms
Intensity
prof
iles
St
atis
tica
l nu
meri
cal
outp
uts
Mensuration
output
Tables of:
Cate
gori
zati
on gr
oup
accu
racy
Means
separation in feature
spac
eAr
eas
and
cont
ents
Co
vari
ance
mat
rix
Tran
sfor
mati
on co
efficien
ts
Cluster
plots
(pla
nned
) Histogram
(Opt.)
Cate
gori
zati
on ac
cura
cy table
Status mo
nito
r Hi
stog
rams
(hardware
and
software)
Intensity
prof
iles
Cl
uste
r pl
ots
(pla
nned
)
512x512
(480
lines
visible)
Four
8-bit ch
anne
ls su
per-
impo
sabl
e with e
ight
1-
bit
themes
Bias
, gain,
inve
rt fo
r al
l CRT
guns
Moving w
indow
(Opt
.)
Time
-lap
se d
ispl
ay (O
pt,)
La
rge-
scre
en display (O
pt.)
Ad
diti
onal
cha
nnel
s (O
pt.)
Hi
gh r
esolution
display. 850X
870
(Opt
.)
320x240
"moving
window"
3 channels,
3 bits/c
hann
el
3 bi
ts/c
olor
512x512
"moving window-scroll"
colo
r
Yes,
in
various colors
Yes
Yes
TAHL.'.
4SYSTEM OUTPUTS
Page
1
of
2 (C
onti
nued
)
OUTPUT
ESL
IDIMS
COMr
Al,
SI-R
ItS
9(I
SI SYSTEM,470,
SAND
VOLATILE D
ISPL
AY
Grap
hics
Two-dimensional
grap
hic
disp
lay
CRT di
spla
y -
grey sc
ale or
co
lor
image
N)
OB
Annotation
Tektronix
(T)
Grey level
disp
lay
(D)
Yes
(Opt
iona
l)
Cluster
(T)
Hist
ogra
ms (D
) Intensity
profiles (D
) Strata b
ound
arie
s from e
xt,
digitizer
(T,
D)
Scat
terg
rams
(T
)
Histogram
Covariance m
atrix
512x512
3, 8-bit
imag
es4,
1-bit
graphics,
color
"Scr
olli
ng"
Alte
rnat
e - field
TV stereo
view
ing
with 3
-D men
sura
tion
soft
ware
(O
pt.)
Flexible Isometric
Display
(Opt
.)
512x
512
4 8-
bit
images
4 1-
bit
grap
hics
"Scrolling"
Yes
- Co
lor
Yes
Yes
Cova
rian
ce matrix
Cluster
plots
Scat
terg
rams
Most
ot
her
syst
em ta
bles
640x
480
7 8-
bit
channels
(512x512 4
8-bit
channels wi
th8
1-bit
overlays,
dynamic
translation, scaling)
Scrolling, su
b-in
uiyc
se
lect
ion
and
reve
rsal
(SAND)
Pseu
do 3-D
isometric
disp
lay
with
variable rotation,
reli
ef,
incl
inat
ion
and
5xmag. (depth cueing -
SAND
) Large
scre
en display
(Opt.)
"Mov
ie Mode" available
with
video
disc
st
ore
(470)
Yes
- li
mite
d to operator
ente
red
free-hand
over
lays
(v
ia v
ideo
mask) (fully
soft
ware
su
ppor
ted
- SAND)
TABL
E 4
SYST
EM O
UTPU
TS (SOFTWARE
SYSTEMS)
Page
1
of
2 (Continued)
OUTP
UT
VOLA
TILE
DI
SPLA
YGr
aphi
cs
Two-
dimensional
grap
hic
disp
lay
CRT
disp
lay
- grey s
cale o
r co
lor
imag
e
Anno
tati
on
* No
t in COSMIC
KANDIDATS
No Pseudo 3-D
Yes
No
JPL
VICA
R
No
*Covariance
matr
ix
Clus
ter
plotting
*512
x512
co
lor
Comtal
* 10
24x1
024
B/W
Comtal
*640x512 B/W
RAMTEK
Yes
,' LARSYS
.'
No No Yes
(at
LARS and
in cosmic
software)
No (at
term
inal
s via
land
li
ne)
No
M
IO
TABLE
4SY
STEM
OUT
PUTS
Page
2 of
2
OUTP
UTGK
I MACK
100
BUNDIX M
DAS
SYST
EM 4
01
HARD
COPY
OUTP
UTS
Line
pr
inte
r
High
qua
lity
film -
grey sc
ale,
color
Over
lays
(Raster)
Maps (Line
Plotter)
Phot
ogra
phs
of display
Goii
ld pr
inte
r/pl
otte
rdonId
prin
ter
(Opt.)
Yes
Dicorned (O
pt.)
Ha
lfto
ne by
dot
matr
ix on
Gould
printer
Optronics
Inte
rfac
e for
Optronics
available
Geom
etri
call
y co
rrec
ted
and
scaled tr
ansp
aren
cies
(O
pt.)
Di
come
d film re
cord
er (O
pt.)
Geometrically
corrected
and
scaled
Optronics
Geom
etri
call
y corrected
and
scaled - Ta
pe output fo
r Dicomed
D163 (p
lann
ed)
Xynctics plotter
(Opt,)
Calc
omp
Planned
Yes
Yes
Yes
TABL
E 4
SYST
I-M OU
TPUT
SPa
8c
2 of _L_1Continued)
OUTP
UT
HARD
COPY O
UTPUTS
Line pr
inte
r
High quality fi
lm -
gr
ey scale,
color
Over
lays
(R
aste
r)
Maps
(Line
plot
ter)
Photog
raphs
of display
ESL
IDIMS
Yes
Also pr
inte
r/pl
otte
r
Yes
- ESL dr
um recorder
Interface
(B/W)
soft
ware
to
Uico
med,
Optronics
Up to 8x10 tr
ansp
aren
cies
ge
omet
rica
lly
corrected
and
scaled
Off-line Xynetics
Opti
onal
COMT
AI,
SHR1
P.S
9
No Yes
No Opti
onal
ISI
SYST
EM 4
70,
SAND
Electrostatic
prin
ter/
plot
ter
Laser
reco
rder
(Planned)
Opti
onal
- user-specified
brand
Up t
o 8x
10 t
rans
pare
ncie
s
Prin
ter /plotter st
d.
Xyne
tics
opt
iona
l
Yes
TABL
H
4SY
STF.
M O
UTP
UTS
(S
OFT
WA
RE
SYST
EMS!
' .P
age
2 of
2 (C
onti
nued
)
OUTP
UT
HARD
COPY OUTPUTS
Line
pr
inte
r
High qu
alit
y film - gr
ey
scal
e, co
lor
Overlays
(Ras
ter)
Maps (Line
Plot
ter)
Phot
ogra
phs
of d
ispl
ay
* No
t in CO
SMIC
KANDIDATS
Grey sc
ale
by overprint
Inte
rfac
e so
ftwa
re for
Di cor
ned co
lor
via
tape
.JPL
VICAR
Yes
Interface
software fo
r;
*Dicomcd color
PDS
flatbed
- Model
1010
Optr
onic
s dr
um scanner
Up to 8x10 tr
ansp
aren
cies
(off-line)
Calcomp
Sepa
rate
hi
gh-q
uali
ty
Polaroid output
'' LARSYS
''
Yes
*Yes
*Yes
*Yes
TABLE
5OTHER
SYSTEM FE
ATUR
ESPage
1 of
1
CH IM
AGE
100
Rl-N
DIX MDAS
SYST
EM,
101
MICROPRO
GRAM
MABL
E PR
OCES
SOR
Planned:
Spec
tral
pr
epro
cess
ing
Clas
sifi
cati
on
Trai
ning
Spat
ial
vide
o filtering
Them
e filtering
Yes
(MCP -
the
Rend
ix ha
rdwa
re
proc
esso
r)Pl
anne
d ar
ray
processor
for;
Supv.
clas
sifi
er
Geom
etri
c resampling
PRES
ENT
COMP
UTER
POP
11/3
5, 11/45
POP
11/7
0 (Opt.)
32K wo
rd /DO
S/35
or
45
64K word/RSX11/35 or 45
Up to 1 Mw RSX/11/70
(1 word =
2 bytes)
POP
11/3
5 (11/45,
11/7
0)
32K/
DOS
Up to 128K core words
RSX11M (Opt.)
(1 word =
2 bytes)
HP 30
00128K by
tes
core min
SOFTWARE
Lang
uage
Modu
lar
Inte
rfac
e mo
de t
o an
alys
t
FORT
RAN
IV (9
0%)
PAL
(10%
)FO
RTRA
N IV (8
0%)
MACRO
(20?
i)
Yes,
Yes
Batc
h (Opt.)
Interactive
Menu
Batc
hInteractive
Menu
Suppor
ts m
ulti
ple
user
s?Ye
s, multiple c
ompl
ete
user
st
atio
ns
FORT
RAN
IV (applications)
SPL
(sys
tem)
Yes
Batc
h Interactive
Menu (Opt.)
Comm
and
Yes
SPECIALIZED
FEATURES
Fast
I/
O for displayed
data
st
orag
e on
ta
pe -
8 sec. fo
r 512x512, 4
chan
nel
Area
ta
ble
outp
ut
- Land us
e by
designated area
Digi
tal
tape im
ages
E-W r
escan-
ned
by T
opo. qu
ad.
Nearest
neig
hbor
sc
an t
o us
ersp
ecif
ied
resolution
Pr
opri
etar
y interpol
atio
n
TAU
Ll-
5O
T1II-
R SY
STH
M
IMiA
TUUH
SPa
ge
1 o
f 1
(Con
tinu
ed)
MICROPROGRAMMABLE
PROC
ESSO
R
PRES
ENT
COMPUTER
SOFTWARE
Language
Modu
lar
Interface
mode
to
anal
yst
Supports m
ulti
ple
users?
SPECIALIZED
FEAT
URES
ESL
IDIM
S
ASAP
: ESL's
prog
ramm
able
array
proc
esso
r 1)
Ma
ximu
m li
keli
hood
2) Fourier
3) Re
samp
ling
4)
Cl
uste
ring
5) Spectral ratios
HP 3000 Series II
12
8K-
bytes
core min.
HP 21Mx also re
quir
ed w
ith
. AS
AP as
a
controller
50 M
By d
isc
min.
recomm.
FORTRAN
IV
SPL
(HP-
3000
)
Yes
Batc
h Interactive
Menu
Co
mman
d
Multiple complete u
ser
stations
Inte
ract
ive
resource inven
tory system
(Opt.)
Map da
ta from e
xter
nal
coor
di
nate
di
giti
zer
Imag
e catalog
5 retrieval
systems
(Opt
.)
COMT
AL SKR1T.S
9
No POP
11/3
5
MACR
O 11
Yes
Interactive
Command
'isi
SY
STEM
*470, SAND
No - System 470
(yes,
vector,
matr
ix and
neig
hbor
hood
op
erat
ions
-
SAND
)
POP
- 11
/35
32K
words
11/7
0 optional
(1 word =
2 bytes)
FORT
H hi
gh le
vel
(85%)
code (15%)
Yes
- User ex
tens
ible
Batc
h Interactive
Command
(Men
u -
SAND)
Multiple complete us
er
stat
ions
(Opt., SA
ND)
Tree
- structured directory
for
images and
data
2
- 80MB d
iscs
standard
TABL
E 5
OTl
ll-H
SY
STliM
H
:ATU
Kl:S
(S
OI-T
WA
KI:
SYST
LMS)
I'agu
1
of
1 (C
onti
nued
)
KAND
IDAT
SJP
L V
ICA
RLA
RSYS
MIC
ROPR
OGRA
MM
ABtE
PRO
CESS
ORIB
M
2735
-MSP
fo
r co
nvol
utio
nNo
PRES
ENT
COMPUTER
POP-15 at KU
Could
go o
n any mi
ni-c
ompu
ter
24K
core m
inim
um
IBM
360/44
128K
core
360/65
1000
K core
360/67 un
der
CP 67
500K min
imum
SOFTWARE
Language
Modu
lar
Interf
ace mode t
o an
alys
t
Fortran
Fortran
IV (70%)
Asse
mbly
(3
0%)
Yes
Yes
Batc
hIn
tera
ctiv
eMe
nu a
nd C
ommand S
tring
Batch
inte
ract
ive
Command
Fortran
IV (8
0%)
Syst
em/3
60 A
ssembler (20%)
Yes
Batc
hInteractive
Comm
and
SPEC
IALIZED
FEATURES
Interactive
image
editor
Image
Based
Information
Syst
em
(IBI
S)Available
for re
mote
terminal
oper
atio
n Well documented so
ftwa
re,
with
trai
ning
aid
s
Not
in C
OSMIC
DEFINITIONS
These definitions are generally arranged in the order in which they occur
in the tables. Definition of all the terms used is not possible within
the scope of this paper.
GENERAL PURPOSE IMAGE PROCESSING (Table 1): The entire gamut of possible
operations on a picture, including radiometric and geometric alterations,
various diagnostic procedures and displays, image analysis, and enhance
ments such as contrast stretching and spatial filtering. This includes
all of the processes leading to the extraction of useful information from
an image such as mapping, radiometric information extraction, multispectral
analysis and classification, calibration and application of calibration
data (rectification), change detection, and image data base operations.
This does not imply that all systems have all of these functions, nor that
the list is necessarily complete.
Radiometric Correction - Application of calibration data or cosmetic cleanup
to remove visible radiometric artifacts.
* Landsat debanding - Landsat imagery generally suffers from a banding
effect due to unbalance in the various sensors. This may be mitigated
by application of calibration data or by line-by-line cosmetic cleanup.
* Photographic Correction - Framing cameras produce non-uniformity of
radiometric response over the face of the images. This shading may be
removed if calibration data is available.
* Other - Pixel noise may be removed by frame-to-frame averaging.
36
Atmospheric radiometric distortions require special procedures to
estimate and correct.
Digital Level Slicing - Conversion of the brightness or digital number (DN)
continuum to series of steps in each of which an assigned DN is substituted
for a range of original DN. Each step may later be assigned a unique color.
Contrast Stretch - An alteration of the DN scale, usually to convert an
input restricted DN range to an expanded output DN range. This may be
linear or non-linear, as desired. Usually done by table lookup for
computer efficiency.
Geometric Corrections - All sensors will produce images with some geometric
warping. A primary example is the Landsat MSS, which, being a line scanner,
requires 14 types of corrections.
* Internal - The principal MSS corrections required are those for inter-
sensor pixel displacements, non-linearity of the scan itself and
horizontal/vertical unequalities in the pixel spacing. Also, for
framing cameras, raster, film, and lens distortions must be corrected.
* External - Correction for external effects such as spacecraft attitude
and altitude, projection onto the round Earth, Earth rotation, and the
various warpings required to register images to maps or to other images.
Geometric Warping - The geometric warping process is broken into two parts:
determination of the warping function required over the face of the image,
and the interpolations of DN required to generate the matrix of output pixels
37
Registration - Determination of the geometric warping function.
* Registration Parameters - Determined either by a mathematical modeling
of the warping desired, or by locating a series of control points (CP)
for which the true locations (e.g., on the ground "Ground Control
Points, (GCP)" or in a reference scene or framework "Relative Control
Points, (RCP)") are known both externally and by line and pixel.
* Mapping CPs to Scene - Specific location of the source of data for
each output pixel is required. The relatively sparse group of CP
locations over the face of an image are used, generally by some sort
of interpolation or mathematical formulation, to generate the required
continuous function.
* Temporal and Mapping - For temporal overlay, CPs are often determined
by cross-correlation of areas in the new and reference scenes. For
mapping, image-type references are not normally available, and CP
selection must be manual.
Geometric Interpolation Techniques - Source location for an output pixel is
rarely precisely at an input pixel location, so that some form of inter
polation using a group of input pixels surrounding the required source
location is required to estimate the DN of the scene at the source location
Filtering - Spatial filtering is used to restore the high spatial
frequencies which have been attenuated in the imaging process, to sharpen
visible edges, to determine areas of high or low DN variance, to soften
noise effects, to remove banding, or for numerous other functions. Spatial
38
filtering is generally done by convolution, but may be accomplished by
multiplication in spatial frequency space via a Fourier transform. Golay
filtering minimizes isolated pixel noise in homograms (thematic maps).
Transforms - Normal image coding records the brightness at each discrete
instantaneous field of view, IFOV, in the scene as the DN in each pixel.
However, the energy in the scene may be grouped in other ways: the
Fourier transform displays the two-dimensional energy content of the
various spatial frequencies present in the scene; the Hadamard transform
displays a related quantity based on square-wave decomposition of the
image. Other transforms are possible and sometimes used.
MULTISPECTRAL ANALYSIS (Table 2): That set of operations involving the
analysis of multispectral data utilizing the spectral information.
"Multispectral analysis" is often used synonomously with "multispectral
classification," although it properly covers all of the required operations
involving multispectral data. Multispectral classification is the recogni
tion of areas of uniform ground cover through recognition of the spectral
signatures (the multispectral vector of DN for a given material).
Classification usually results in the substitution in each pixel of a
"name" or color representing the ground cover class in place of the
original data.
Supervised Classifier - The computer is instructed as to the identification
of certain known materials in the scene by the use of "training areas".
It is then given decision rules, and instructed to display all pixels
matching the series of materials by unique codes (or colors).
39.
Unsupervised Classifier - The computer first groups into a series of
classes all of the pixels in the scene by measuring the tendency of
pixels of a given material to cluster around a given location of multi-
spectral space. Following this, the analyst identifies each material.
* Region growing - Pixels of a given material tend to form a series of
groups of contiguous pixels (in image space). Thus, "All wheat pixels
in the scene occur in a group of wheat fields, each of which is
identifiable." Region growing is the computer process of gathering
and displaying the pixels in the identifiable groups, after which the
analyst may identify each.
Mensuration - the determination of areas in the image or designated sub
section. This normally is done by simple pixel count, although for some
purposes intra-pixel mixtures must be estimated.
Inter-Band Manipulation - For multispectral data, each spectral image is
a "band." Operations between bands have been found to be useful for certain
analyses.
* Functions - Various algebraic functions such as multiplication or
division are non-linear, and produce data of a new kind. For example,
division of a scene by a reference "flat field" scene, point-by-point,
will tend to normalize against variation of sensor response over the
face of the scene.
* Spectral Analysis - Analysis of selected data points to determine the
optimum processes to be applied to the entire image. Examples are
eigenvector analysis to determine the optimum band combinations to
40
allow multispectral analysis, or the selection of optimum ratios to
be used for display.
* Spectral Axis Rotation - Linear combination of bands, pixel-by-pixel,
amounts to producing a new projection of the data onto a set of
rotated axes. Rotation to the optimum angles following an eigenvector
analysis (Karhunen-Loeve) is the most usual, but other rotation angles
may be used for other purposes.
Statistical Operations - The set of processes and decisions required to
carry out the multispectral analysis.
* Training Field Selection - Operator designation of areas of known
materials or ground cover. May be done interactively or by off-line
mapping.
* Training Statistics - Characterization of the group of pixels of the
training area, usually as mean and variance in multispectral space
(covariance matrix). Other measures such as texture could be used as
a derived multivariate analysis "band" for use with the multispectral.
* Number of Spectral Bands - Analysis time goes up as the number of bands
used increases - but so may the classification accuracy. A tradeoff
to be made by the analyst.
* Maximum Number of Classes - For some classifiers, the time for classifi
cation goes up with the number of classes. Another tradeoff, since the
analyst may group classes together as desired.
41
* Optimum Band Selection - Some bands, including possible ratios between
bands, will give better class identification than will others. Some
software is available to aid the analyst in this selection.
* Speed - Schemes using full analysis can be extremely slow; table lookup
methods can accomplish much the same task at greatly increased speeds.
Decision as to "optimum methods" has not been made, and may not be
possible; differences between methods is often secondary to differences
caused by variance in the scene or the analyst choice of training.
INPUTS (Table 3): In addition to the computer compatible tape (CCT) input
anticipated, other input devices will be useful for other than Landsat
MSS data.
TV Camera - For scanning input images, a local TV camera may be useful.
This normally will be a vidicon or image dissector.
Microdensitometer - For higher accuracy, either in spatial or in brightness
quantizations, various forms of travelling aperture devices are used.
These commonly take the form of either drum scanners or flatbed scanners.
Digital Tapes - The tape format expected for most MSS work is the "NASA
Landsat." Others, many of which are similar, may be encountered. NASA
and USGS are currently trying to define a universal tape format family
which will encompass many of the present formats.
42
Analog Tapes - For some purposes, image, data may be recorded on analog
magnetic tapes. Special analog-digital conversion is required to utilize
: this data.
OUTPUTS (Table 4): These may be either volatile on a terminal display,
or hard copy via line printer, image film, maps, or tables.
» Volatile outputs&
1 * Graphics - A number of graphics displays are available - these are
normally used for alphanumeric conversations with the analyst during
the analysis process.
* Two-Dimensional Graphics - Some graphics terminals have the ability to
display line drawings, graphs, cluster plots, and other diagnostic aids
* CRT for Image Display - When grey-scale or color images need to be
displayed during the analysis, a special television-like terminal
display is required. These displays must be continually "refreshed",
requiring a special memory in the system to continually generate the
required data.
* Annotation - Ability to superimpose grids, alphanumeric data and other
information on a displayed image.«t
j9 t Hard Copy Outputs
* Line Printer - The normal computer printer, which may also be used to
generate a grey-scale image by character selection and overprinting.
For a printer having the normal 10 characters/inch and 6 lines/inch,
43
a 1/24,000-scale image will be produced if the pixels are interpolated
to be 60.96x101.60 meters IFOV.
* Film - For most analysis, the desired output product will be high
quality film, either in black/white (B/W) or color. The latter will
normally be generated by photographic combination of three B/W films.
* Overlays - Film output requiring the ability to convert some set of
data such as polygon vertices to rasters.
* Maps - Output implying the capability of driving line drawing devices.
* Display Photographs - Usually for quick look or reduced-quality
permanent copy, limited in quality by the display device.
OTHER FEATURES (Table 5)
Microprogrammable Processor - Some of the analysis steps are very time-
consuming, even with fast general purpose computers. A number of special
purpose devices are available to perform specified process very efficiently.
These are usually used as peripheral devices to the normal computer in the
system,
Present Computer - The hardware systems discussed each are based on a modern
minicomputer. Depending on the degree of interaction, number of terminals
serviced, displays, and other features, the size required may vary consider
ably.
Software - Most applications programs are written in Fortran. Various
higher-level languages may be used for parts of the system programs, and
for some of the applications. The feature to look for here is the ability
44
I
of the user to write and incorporate new programs as he wishes, since
all functions cannot be defined at purchase time, and the state-of-the-
art is continually advancing.
* Interface Mode to Analyst:
1. Batch - The analyst generates a series of commands, either at an
interactive terminal or via card job entry. The entire series is
run by the computer as a single job without further interaction
with the analyst.
2. Interactive Command - The computer carries out each command as it is
entered by the analyst, (usually) displays the results, and waits
for the next command. In some cases, it may be possible to assemble
or call a short series of commands (a procedure) which will be
accomplished before receiving the next command.
3. Interactive Menu - As each command is entered by the analyst, the
computer replies with a display which gives the analyst the choice
of a number of options. These might be parameter entries, function
options such as linear, log, table, or other defined types of con
trast stretch, or entries relating to any multiple choice decisions
the analyst must make. This mode is of particular value to the
analyst unfamiliar with the details of the function being called,
as it guides him through the required decisions.
45
I HATP mTc512M8551988 MOSS, Marshall E.
AUTHOR ~~~
Water Resources in the 21st
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