Paper
6 April 1995 Extraction of water regions from radar imagery using a discrete biorthogonal wavelet transform
Richard A. Hevenor, Eugene A. Margerum
Author Affiliations +
Abstract
A discrete biorthogonal wavelet transform is used to extract water regions from radar imagery. A family of discrete scaling vectors and wavelets are formulated by direct construction and used to create a multiresolution image pyramid from an input radar image. The scaling vectors and wavelets each have eight nonzero elements. A second set of vectors is used to perform the inverse transform and obtain an image. Various sections of the pyramid are used to reconstruct images which resemble the original image except at reduced resolution. In this way a small image `cube' is built up. Feature vectors are formed from the image cube such that the dimension of each feature vector is equal to the number of images in the cube. These feature vectors serve as input data to two standard clustering routines. The clustering routines are the minimax and the K-means. These clustering routines are used to place each pixel of the original image into one of two classes: water or land. Finally a simple routine is performed to try and correct any obviously misclassified pixels. This technique was applied to synthetic aperture radar images. It was found that when the image cube was calculated from sections of the wavelet transform high up in the pyramid the shadow regions on land blended in with the rest of the terrain but large water bodies could still be extracted intact. The results of applying this procedure to two synthetic aperture radar images are shown.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard A. Hevenor and Eugene A. Margerum "Extraction of water regions from radar imagery using a discrete biorthogonal wavelet transform", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205434
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Cited by 1 scholarly publication.
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KEYWORDS
Radar

Wavelets

Wavelet transforms

Synthetic aperture radar

Image resolution

Silicon

Speckle

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