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| Citation: | null doi: 10.12000/JR19108
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Abstract
“Contrast” is an generic denomination for “difference”. Measures of contrast are a powerful tool in image processing and analysis, e.g., in denoising, edge detection, segmentation, classification, parameter estimation, change detection, and feature selection. We present a survey on techniques that aim at measuring the contrast between (i) samples of SAR imagery, and (ii) samples and models, with emphasis on those that employ the statistical properties of the data. -
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References
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1 https://www.harrisgeospatial.com/Software-Technology/ENVI/ 2 https://step.esa.int/main/toolboxes/snap/
1https://step.esa.int/main/toolboxes/polsarpro-v6-0-biomass-edition-toolbox/
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- Figure 1. Mind map of this review contents
- Figure 2. Exponential densities with mean 1/2, 1, and 2 (red, black and blue, resp.) in linear and semilogarithmic scales
- Figure 3. Unitary mean Gamma densities with 1, 3, and 8 looks (black, red, and blue, resp.) in linear and semilogarithmic scales
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Figure 4. Densities in linear and semi-logarithmic scale of the
${\rm E}(1) $ $ {{\cal{G}}^0} $ $ \alpha\in\{-1.5,-3.0,-8.0\} $ -
Figure 5. Densities in linear and semilogarithmic scale
$ {\cal{G}}^0(-5,4,L) $ $ L\in\{1,3,8\} $ - Figure 6. Equalized intensity data with grid
- Figure 7. Regression analysis for the estimation of the equivalent number of looks
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Figure 8. Strips of 10 × 500 pixels with samples from two
$ {\cal{G}}^0 $ - Figure 9. Illustration of edge detection by maximum likelihood
- Figure 10. Illustration of parameter estimation by distance minimization
- Figure 11. Illustration of the Nonlocal Means approach