Title :
Image Denoising Algorithm Based on Improved Filter in Contourlet Domain
Author :
Li, HongJun ; Zhao, Zhimin
Author_Institution :
Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
fDate :
March 31 2009-April 2 2009
Abstract :
In this paper we analyzed directional filter and pyramid filter in Contourlet transform, confirmed the different choices of filters directly affect the image denoising result, so we constructed a kind of compactly supported biorthogonal filter based on human visual Characteristics and applied it to image denoising. The new Contourlet transform algorithm can improve the result of image denoising, and the most important improvement is the great superiority shown by new Contourlet domain hidden markov tree (CHMT) algorithm in image denoising. The denoised images by using new CHMT algorithm have been improved on PSNR.
Keywords :
digital filters; hidden Markov models; image denoising; Contourlet domain; biorthogonal filter; directional filter; hidden markov tree algorithm; image denoising algorithm; pyramid filter; Algorithm design and analysis; Computed tomography; Humans; Image analysis; Image denoising; Laplace equations; Noise reduction; Optical filters; Optical noise; Wavelet transforms; CHMT; Contourlet transform; Image denoising;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.510