Title :
PolSAR image speckle reduction based on sparse representation and structure characteristics
Author :
Ping Han ; Xiaohong Yu ; Xiaoguang Lu ; Hai Li
Author_Institution :
Tianjin Key Lab. for Adv. Signal Process., Civil Aviation Univ. of China, Tianjin, China
Abstract :
This paper presents a novel speckle reduction algorithm based on sparse representation and structure characteristics of PolSAR image. First, each pixel in original image is classified into bright point or line targets, dark point or line targets and others to form a classification map. Second, sparse decomposition and reconstruction is performed on PolSAR image by OMP and K-SVD methods to filter speckle. Finally, the blurred point and line targets in filtered image are enhanced with the classification map. Experimental results with the data of Hayward area from AIRSAR system show that the proposed method is effective both on speckle reduction and scattering characteristics preservation.
Keywords :
image classification; image denoising; image enhancement; image reconstruction; image representation; radar imaging; speckle; synthetic aperture radar; AIRSAR system; Hayward area; K-SVD methods; OMP; PolSAR image; blurred point; bright point; classification map; dark point; line targets; scattering characteristics preservation; sparse decomposition; sparse reconstruction; sparse representation; speckle reduction algorithm; structure characteristics; Classification algorithms; Dictionaries; Filtering; Image reconstruction; Noise; Speckle; Synthetic aperture radar; PolSAR image; polarimetric characteristics; sparse representation; speckle reduction; structure classification map;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
DOI :
10.1109/ICASSP.2014.6855188