Title :
An improved wavelet-based method for SAR images denoising using data fusion technique
Author :
Chen, Guozhong ; Liu, Xingzhao
Author_Institution :
Dept. of Electron. Eng., Shanghai Jiao Tong Univ., China
Abstract :
A speckle reduction algorithm for synthetic aperture radar (SAR) images based on the wavelet transform can keep the detail of the image well, but it cannot do well enough at the speckle reduction. However, those statistical filters, such as Lee Filter, outperform at speckle reduction in the uniform region. To make use of the advantages of the both filters, in this paper, we proposed an improved wavelet-based method for SAR image denoising by combining these two kinds of methods and using the data fusion technique according to a certain fusion rule. The experimental results show that this new method can reduce the speckle and maintain the image detail better simultaneously.
Keywords :
filtering theory; image denoising; radar imaging; sensor fusion; synthetic aperture radar; wavelet transforms; SAR image denoising; data fusion technique; speckle reduction algorithm; statistical filter; synthetic aperture radar; wavelet transform; Additive noise; Data engineering; Degradation; Filters; Image denoising; Image processing; Reactive power; Speckle; Statistics; Wavelet transforms;
Conference_Titel :
Radar, 2006 IEEE Conference on
Print_ISBN :
0-7803-9496-8
DOI :
10.1109/RADAR.2006.1631898