7 elements of remote sensing process 1.energy source (a) 2.radiation & atmosphere (b)...
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7 elements of remote sensing process
1. Energy Source (A)
2. Radiation & Atmosphere (B)
3. Interaction with Targets (C)
4. Recording of Energy by Sensor (D)
5. Transmission & Reception (E)
6. Interpretation and Analysis (F)
7. Application (G)
Extract meaningful information from imagery
6. Interpretation and Analysis (F) - the processed image is interpreted, visually and/or digitally, to extract information about the target which was illuminated.
4.3 Digital Image Processing
Common image processing image analysis functions:
A. Preprocessing
B. Image Enhancement
C. Image Transformation
D. Image Classification and Analysis
Background
• DIP - manipulation & interpretation of
images
• Began in 1960’s
• 1972 - Landsat 1 launched
• Access to low cost, efficient computers
• Access to imagery
Digital spatial image - made up of a grid of cells, each containing a value or measurement and representing an area of the Earth’s surface.
Pixel
Digital Number (DN) - value stored within a pixel
of an image, represents amount of light
reflected back to sensor.
digital format – images are represented in a
computer as arrays of pixels.
Multispectral images - multiple layers representingdifferent parts of the EMS.
4.2 Elements of Visual Interpretation
• Identifying targets
– Based on how they reflect/emit radiation
• Based on;
– Visual elements – tone, shape, pattern,
texture, shadow, association.
4.3 Digital Image Processing
Common image processing image analysis functions:
A. Preprocessing
B. Image Enhancement
C. Image Transformation
D. Image Classification and Analysis
1. Pre-Processing (Image Rectification)
• Initial processing of raw data prior for analysis
• Correct for distortion due to characteristics of
imaging system & imaging conditions.
1. Pre-Processing (Image Rectification)
• Procedures include:
a. geometric correction - correct for geometric distortion due
to Earth's rotation, curvature, platform motion, relief
displacement, (such as oblique viewing).
b. radiometric correction - correct for uneven sensor
response over image, random noise, atmosphere.
c. geo-referencing - ground control points (GCP's) used to
register image to a precise map.
2. Image Enhancement
• Solely to improve appearance of imagery.
• Increasing visual distinction
• Un-enhanced images usually appear very dark -
little contrast - difficult to visually interpret.
• Various procedures applied to image data in order to
more effectively display data for visual
interpretation.
2. Image Enhancement
A. Contrast stretching
– Histograms
– Increase tonal distinction
B. Spatial filtering
– Enhance/suppress features
A. Contrast stretching
• Radiometric enhancement - manipulate
brightness and contrast of pixels to amplify
differences between features.
• Changes made to pixels without
consideration of values of surrounding
pixels.
– adjust brightness and contrast controls
– apply preset contrast stretches
– manually adjusting image histograms
A. Contrast stretchingRadiometric Enhancement
• Not all values will be used or spread out to fill the entire range of 256 values.
• Need to manipulate the relative brightness and contrast of the pixels to amplify the differences between features.
Lanier.img (4-3-2)
Swipe
• Computers - ideal for manipulating
and analyzing large continuous
data sets displayed as grayscale.
• Used to distinguish between slight
spectral variations and enhance
them.
Landsat 7 image with no contrast stretching - histogram for the near infrared
band.
Some features, like agricultural areas, can be distinguished.
Applying a histogram stretch produces a simple classification of urban, agricultural, and mixed use areas.
A. Contrast stretchingRadiometric resolution
• Dynamic range or number of possible data
values (Digital numbers) in each band of
the image.
• The range of DN’s is usually referred to by
the number of bits into which the recorded
energy is divided.
• 28 = 256 is most common
0 = black255 = white
A sensor measures the electromagnetic energy within its range.
Total intensity of the energy from zero to the maximum is broken down into 256 brightness values for 8-bit data.
A. Contrast stretchingLinear grey-level stretching
• Lower threshold value is chosen so that all pixel values
below threshold are mapped to zero.
• Upper threshold value is chosen so that all pixel values
above threshold are mapped to 255.
• All other pixel values are linearly interpolated to lie
between 0 and 255.
– Lower and upper thresholds are usually chosen to be values close to the
minimum and maximum pixel values of the image.
Two types of histogram stretches
Landsat TM image - Olympic Pennisula, NW Washington
Vis red band