CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
A modified SLT denoising method
Chen Xi.; Peng Silong; Xi Chen
2008
Conference NameSITIS 2008
Pagespp 430-434
Conference Date2008/11/30-2008/12/3
Conference PlaceIndonesiaBali Indonesia
AbstractWavelet shrinkage denoising has been investigated for a long time due to its simplicity and good results. SLT denoising proposed by Yacov Hel-Or et al. recently generates mapping functions (MFs) also known as shrinkage function which are learned directly from example images using least-squares fitting. In this paper we design MFs with the prior information properly incorporated in SLT denoising. Since coefficients in the same wavelet subband have different statistic characteristics we first classify wavelet coefficients into different classes. Then MFs for different regions are deduced with corresponding prior model. Experimental results give a direct show that the proposed method obtains higher PSNR (Peak Signal to Noise Ratio) and improve visual quality of the denoised images.
Keyword
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12884
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorXi Chen
Recommended Citation
GB/T 7714
Chen Xi.,Peng Silong,Xi Chen. A modified SLT denoising method[C],2008:pp 430-434.
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