Polarimetric synthetic aperture radar (PolSAR) images are disturbed by an inherent noise having multiplicative properties called “speckle.” This noise is undesirable, and its treatment is difficult. To reduce the speckle, a polarimetric filtering is necessary to improve the image quality. The purpose of PolSAR filtering is to use the polarimetric information in the different channels to develop an efficient algorithm adapted to this data type, to reduce well the speckle and preserve the contained information. We present the PolSAR wavelet filtering applying the stationary wavelet transform: filtering by multiscale edge detection with two improvement techniques of wavelet coefficients, filtering by wavelet thresholding using the hard and soft thresholding and their two enhanced versions. Our contribution is based on the adaptation of wavelet thresholding to PolSAR data and on improvement techniques to filter polarimetric covariance or coherency matrix elements and span. The methods are applied to the fully polarimetric RADARSAT-2 images acquired over Algiers, Algeria (C-band), to the three polarimetric E-SAR images acquired on Oberpfaffenhofen area located in Munich, Germany (P-band), and to the simulated PolSAR images (L-band). We evaluate the performance of each filter based on the following criteria: smoothing homogeneous areas, preserving contours, and polarimetric information. Experimental results and a comparative study are included.
The speckle reduction problem for polarimetric synthetic aperture radar images is a complex issue due to difficulties on preserving polarimetric information. Several filters have been developed for this purpose such as Novak filter, enhanced Lee filter, and wavelet filters. We present an improved version of the Li filter by adding two false alarm detectors to enhance target appearance. These detectors are applied according to the homogeneity nature of the area to filter. The filtering process is performed by carrying a filtering step for each part of the SLC SAR image, intensity, and phase, independently from each other and using a contour detection technique to maintain the linear structures in the images. A comparative study with enhanced Lee filter is done and allows to conclude that introducing constant false alarm rate detectors gives the expected results: better targets (or reflectors) preservation, smoothing homogeneous regions, and details preservation.
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