|A modified SLT denoising method|
|Chen Xi.; Peng Silong; Xi Chen
|Conference Name||SITIS 2008
|Conference Place||IndonesiaBali Indonesia
|Abstract||Wavelet 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.|
|Corresponding Author||Xi Chen|
Chen Xi.,Peng Silong,Xi Chen. A modified SLT denoising method[C],2008:pp 430-434.
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