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2013 (Vol. 6, Issue: 18)
Article Information:

Image De-Nosing Based on Non-Subsampled Contourlet Transform Domain in Multi-Bessel K Form Model

Ping Jiang and Hao Sha
Corresponding Author:  Ping Jiang 

Key words:  Image de-nosing, multi-bessel K form model, Non-Subsampled Contourlet Transform (NSCT), Structural Similarity (SSIM), , ,
Vol. 6 , (18): 3400-3403
Submitted Accepted Published
January 19, 2013 February 22, 2013 October 10, 2013
Abstract:

This study proposes a new image de-nosing algorithm based on Non-Subsampled Contourlet Transform (NSCT) domain in multi-Bessel k form model. Firstly, the noisy image is decomposed into a set of multi-scale and multidirectional frequency sub-bands by NSCT, according to BKF model to scale coefficient of intra-scale and inter-scale processing, fully considering correlation of internal and external scale. Lastly, the estimated coefficients are updated according to inverse non-subsampled Contourlet transformation is performed to get de-noised image. Experimental results show that out algorithm better than the other algorithms in peak signal-to-noise ratio, structural similarity and visual quality.
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  Cite this Reference:
Ping Jiang and Hao Sha, 2013. Image De-Nosing Based on Non-Subsampled Contourlet Transform Domain in Multi-Bessel K Form Model.  Research Journal of Applied Sciences, Engineering and Technology, 6(18): 3400-3403.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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