Image Denoising Based on Non-Local Means and Multi-scale Dyadic Wavelet Transform
A variety of wavelet transform methods have been introduced to remove noise from images. However, many of these algorithms remove the fine details and smooth the structures of the image when removing noise. The wavelet coefficient magnitude sum (WCMS) algorithm can preserve edges, but it is at the expense of removing noise. The Non-Local means algorithm can removing noise effective. But it tend to cause distortion ( eg white). Meanwhile, when the noise is large, the method is not so effective. In this paper, we propose an efficient denoising algorithm. we denoised the image with non-local means algorithm in the spatial domain and WCMS algorithm in wavelet domain, weithted, combined them and got the image that we want. The experiment shows that our algorithm can improve PSNR form 0.6dB to 1.0dB and the image boundary is more clearly.
denoising non-local means wavelet transform multiscale singularity detection
Gang Yu Yong Yin Hongjun Wang Zhi Liu Dengwang Li
School of Information science and engineering Shandong University Jinan China School of Information science and engineering Shandong University Jinan China Department of Radiatio Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan C
国际会议
成都
英文
333-336
2010-07-07（万方平台首次上网日期，不代表论文的发表时间）