5 February 2004 Markovian regularization of Hermite-transform-based SAR image classification
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Abstract
A novel classification scheme for SAR images based on the perceptual classification of image patterns in the Discrete Hermite Transform domain has been developed. In order to obtain the DHT referred to a rotated coordinate system the set of coefficients of a given order are mapped through a unitary transformation based on the generalized binomial function. This representation allows a perceptual classification, including constant patterns (0-D), oriented structures (1-D), and non-oriented structures (2-D). Classification is based on light adaptation and contrast masking properties of the human vision. Finally, classification is improved by means of a probabilistic approach based on Markov Random Fields.
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Penelope Lopez-Quiroz, Boris Escalante-Ramirez, Jose L. Silvan-Cardenas, "Markovian regularization of Hermite-transform-based SAR image classification", Proc. SPIE 5238, Image and Signal Processing for Remote Sensing IX, (5 February 2004); doi: 10.1117/12.511402; https://doi.org/10.1117/12.511402
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