A NEW SPECKLE REDUCTION ALGORITHM OF POLSAR IMAGES BASED ON A COMBINED GAUSSIAN RANDOM FIELD MODEL AND WAVELET EDGE DETECTION APPROACH

摘要

An adaptive speckle reduction algorithm for Polarimetric SAR (PolSAR) data, based on the combination of Gaussian Markov Random Field (GMRF) and Wavelet Edge Detection (WED) is proposed in this paper. The algorithm has three major steps: (a) first-time speckle reduction based on the GMRF model, (b) detail preservation using a WED approach, and (c) second-time speckle reduction using a least square approach based on pseudo span image. Both the GMRF and WED use the coherency matrix as the input, which has sensitive diagonal elements, namely T_(11), T_(22) and T_(33) corresponding to surface, double-bounce, and volume scattering, respectively. A key point in the proposed algorithm is that strong point targets are not affected by speckle phenomena and thus, they should be excluded from the de-speckling process. The proposed algorithm is applied to a full polarimetric C-band RADARSAT-2 data in the Avalon Peninsula, Newfoundland and Labrador, Canada.