Title :
Refined denoising method for SAR image in the complex wavelet domains
Author :
Wen, Chenglin ; Gao, Guowei
Author_Institution :
Coll. of Autom., Hangzhou Dianzi Univ., Hangzhou
Abstract :
Addressing SAR image speckle denoising, this dissertation proposes a new method based on dual tree complex wavelet transformation combined with modification to them according to significant coefficient rule. In the method, a thresholding method are adapted for each selected subband based on the nonlinear functions. The nonlinear functions are based on sigmoid functions. And then, the wavelet coefficients are modified according to a rule whether the coefficient is a significant one or not. Experimental results show that our algorithm is among the best for speckle removal.
Keywords :
image denoising; image segmentation; nonlinear functions; radar imaging; synthetic aperture radar; trees (mathematics); wavelet transforms; SAR image speckle denoising; adaptive sigmoid thresholding; dual tree complex wavelet transformation; nonlinear function; refined denoising method; speckle reduction; wavelet coefficient rule; Automation; Continuous wavelet transforms; Discrete wavelet transforms; Educational institutions; Fourier transforms; Noise reduction; Speckle; Wavelet coefficients; Wavelet domain; Wavelet transforms; complex wavelet; speckle reduction; synthetic aperture radar(SAR);
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594572