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Abstract
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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
Submitted: January 19, 2013
Accepted: February 22, 2013
Published: October 10, 2013 |
Abstract:
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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.
Key words: Image de-nosing, multi-bessel K form model, Non-Subsampled Contourlet Transform (NSCT), Structural Similarity (SSIM), , ,
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Abstract
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Cite this Reference:
Ping Jiang and Hao Sha, . Image De-Nosing Based on Non-Subsampled Contourlet Transform Domain in Multi-Bessel K Form Model. Research Journal of Applied Sciences, Engineering and Technology, (18): 3400-3403.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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