A Modified Nonlocal-Means for Adaptive Image Denoising
Image denoising is an important problem and widely studied in image processing. Denoising is a crucial step to increase image conspicuity and to improve the performances of all the processing needed for quantitative imaging analysis. This work presents a modified nonlocal-mean denoising method based on the texture collection and edge information. At last, experiments result illustrate that the technique can be successfully nsed to the classical case of additive Gaussian noise. The proposed algorithm seems to improve on the state of the art performance.
image denoting nonlocal means texture collection edge information PSNR
Ming Yin Shi-Quan Shao Li Ma
School of Electrical and Information Engineering, Southwest University for Nationalities of china Ch School of Computer technology and scienc, Southwest University for Nationalities of china
国际会议
哈尔滨
英文
4224-4227
2011-08-12（万方平台首次上网日期，不代表论文的发表时间）