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Multilevel approaches for the total least squares method in deblurring problems

Malena Español, Tufts UniversityMisha Kilmer, Tufts University

Dianne O’Leary, University of Maryland, College Park

ICIAM 2007 - Zurich, Switzerland

2

Outline Problem Multilevel Method Algorithm Numerical Example Conclusion and Future Work

ICIAM 2007 - Zurich, Switzerland

3

Problem

noiseGaussian additiveunknown contain and

matrix dconditione-ill large, a is

where

,

system theand ,given , Find

bA

RA

bAx

bAx

nm

ICIAM 2007 - Zurich, Switzerland

4

Total Least-Squares Method

rbxEALxrE

rbxEArE

bAx

p

p

p

xE,r

xE,r

)( s.t. min

isn formulatio TLS dRegularizeA

)( s.t. min

solve we, system thesolve To

2

2

2

F,

2

2

2

F,

Regularization by Truncated TLS by Fierro, Golub, Hansen and O’Leary (1997)

ICIAM 2007 - Zurich, Switzerland

5

Classical Two-Level Method

cii

ici

iiii

iTiii

iii

Tiiii

iii

iiii

iii

xxx

rxA

xAbr

ecPxx

reA

PAPA

rPr

xAbr

bxA

Solve""

Solve""

Solve""

1

111

1

1

Pre-Smoothing

Post-Smoothing

Coarse-Grid Correction

Restriction

Prolongation

ICIAM 2007 - Zurich, Switzerland

6

Classical Multilevel Method

cii

ici

iiii

iTiii

iii

Tiiiiiii

iiii

iii

iii

xxx

rxA

xAbr

xPxx

),bV(Ax

PAPArPr

xAbr

bxA

bxA

),bV(Ax

Solve

,

Solve

Else

Solve

gridcoarsest If

function

1

111

11

000

ICIAM 2007 - Zurich, Switzerland

7

Two-level TLS Method

00 , xE

c

c

TT

xxxEEE

rrxEA

ePxxPEPEE

11

1

00101

,~~

~~)~~

(

,~

rreEA ~)~~

( 00

“Post-Smoothing”

Pre-Smoothing

ICIAM 2007 - Zurich, Switzerland

8

Restriction and Prolongation Operators

11000000

00110000

00001100

00000011

11000000

00110000

00001100

00000011

2

2W

Haar wavelet transform V

W1V1

ICIAM 2007 - Zurich, Switzerland

9

Changing basis

.ˆ and ˆ ,ˆ ,ˆ

where

ˆˆˆ)ˆˆ(

have webasis of change aBy

)(

WrrWbbWEWEWAWA

rbxEA

rbxEA

TT

Optical Tomography: Zhu, Wang and Zhang (1998)

ICIAM 2007 - Zurich, Switzerland

10

Properties

A

43

21

ˆˆ

ˆˆˆ

AA

AAA

.ˆin are ˆ of entrieslargest The 3)

.ˆˆ and, symmetric are ˆ ,ˆ then symmetric, is If 2)

Toeplitz. are ˆ and ˆ,ˆ,ˆ then Toeplitz, is If 1)

1

2341

4321

AA

AAAAA

AAAAAT

ICIAM 2007 - Zurich, Switzerland

11

Bandwidth reduction

ICIAM 2007 - Zurich, Switzerland

12

p

p

p

FExxLbxEAE

xEArbxEA

r

r

b

b

x

x

EE

EE

AA

AA

rbxEA

1

2

21111

2

1ˆ,ˆ

22211111

2

1

2

1

2

1

43

21

43

21

ˆˆˆ)ˆˆ(ˆmin

ˆ)ˆˆ(ˆˆˆ)ˆˆ(

ˆ

ˆˆ

ˆ

ˆ

ˆˆˆ

ˆˆ

ˆˆ

ˆˆ

ˆˆˆ)ˆˆ(

11

Pre-Smoothing

ICIAM 2007 - Zurich, Switzerland

13

2

11

3

11

2

1132

4

2

4

2

ˆ

ˆˆ

ˆ

ˆˆ

ˆ

ˆˆˆˆ

ˆ

ˆ

ˆ

ˆ

r

rx

A

EA

b

bxEx

E

E

A

A

Post-Smoothing

p

p

Tp

FFFEEEx x

xLWxEx

E

E

A

AEEE

2

1

2

2

132

4

2

4

22

3

2

4

2

2ˆ,ˆ,ˆ,ˆ ˆ

ˆˆˆˆ

ˆ

ˆ

ˆ

ˆˆˆˆmin

4322

ICIAM 2007 - Zurich, Switzerland

14

Two-Level Method

bA,

p

p

Tp

FFFEEEx x

xLWrxEx

E

E

A

AEEE

2

1

2

2

132

4

2

4

22

3

2

4

2

2ˆ,ˆ,ˆ,ˆ ˆ

ˆˆˆˆˆ

ˆ

ˆ

ˆ

ˆˆˆˆmin

4322

p

p

p

FExxLbxEAE 1

2

21111

2

1ˆ,ˆˆˆˆ)ˆˆ(ˆmin

11

V

V1 W1

xEAbr

VEVExVx TT

)(

ˆ,ˆ 11111

WEE

EEWE

xWxVx

T

TT

43

21

2111

ˆˆ

ˆˆ

ˆˆ

ICIAM 2007 - Zurich, Switzerland

15

Multilevel Method

V

V1

V2

V3 W3

W2

W1

ICIAM 2007 - Zurich, Switzerland

16

Numerical Example

01.1 Operator, DerivativeFirst

)01.0,0( with )~

(

solution edgy :

)1.0,0(~

h matrix wit Toeplitz symmetric, :~

matrix symmetric Toeplitz, Gaussian, :

2

2

pL

bNeexEAb

x

ANEE

A

true

true

ICIAM 2007 - Zurich, Switzerland

17

Numerical Example

truex b

ICIAM 2007 - Zurich, Switzerland

18

Numerical Example

truex

recx

ICIAM 2007 - Zurich, Switzerland

19

Conclusions and Future work

General Cases – Non Structured Matrices

Extension to 2D, 3D Parameter Selection Additional Constraint on E

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