Paper Info
Title
Selective Parameters Based Image Denoising Method.
Abstract
In this paper, we propose a Selective Parameters based Image Denoising method that uses a shrinkage parameter for each coefficient in the subband at the corresponding decomposition level. Image decomposition is done using the wavelet transform. VisuShrink, Sure Shrink, and BayesShrink define good thresholds for removing the noise from an image. Sure Shrink and BayesShrink denoising methods depend on subband to evaluate the threshold value whereas the VisuShrink is a global thresholding method. These methods remove too many coefficients and do not provide good visual quality of the image. Our proposed method not only keeps more noiseless coefficients but also modifies the noisy coefficients using the threshold value. We experimentally show that our method provides better performance in terms of objective and subjective criteria i.e. visual quality of image than the VisuShrink, Sure Shrink, and BayesShrink.
Year
DOI
Venue
2012
10.1007/978-3-642-32063-7_34
INTELLIGENT INFORMATICS
Keywords
Field
DocType
Image denoising,Wavelet coefficient,Thresholding,Peak-Signal-to-Noise Ratio (PSNR)
Noise reduction,Pattern recognition,Computer science,Threshold limit value,Image denoising,Artificial intelligence,Thresholding,Video denoising,Nuclear magnetic resonance,Wavelet transform
Conference
Volume
ISSN
Citations 
182
2194-5357
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Mantosh Biswas1213.42
H. Om29917.56