Research Article | OPEN ACCESS
Image De-Nosing Based on Non-Subsampled Contourlet Transform Domain in Multi-Bessel K Form Model
Ping Jiang and Hao Sha
School of Mathematics, Hefei University of Technology, Hefei, China
Research Journal of Applied Sciences, Engineering and Technology 2013 18:3400-3403
Received: January 19, 2013 | Accepted: February 22, 2013 | Published: 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.
Keywords:
Image de-nosing, multi-bessel K form model, Non-Subsampled Contourlet Transform (NSCT), Structural Similarity (SSIM),
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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