SSIM-based optimal non-local means image denoising with improved weighted Kernel function

In this paper, a novel SSIM-based NLM algorithm is proposed. We replace the exponential weighted kernel function with a cosine coefficient weighted Gaussian kernel function and incorporate the structural similarity (SSIM) index, which is the state-of-the-art image quality assessment measure, into th...

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Bibliographic Details
Published in2017 36th Chinese Control Conference (CCC) pp. 5429 - 5433
Main Authors Lu Zhang, Yuxia Sheng, Li Chai
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, CAA 01.07.2017
Subjects
Conferences
Cybernetics
Europe
image denoising
Image processing
non-local means
Process control
Signal processing
structural similarity index
weighted kernel function
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Summary:In this paper, a novel SSIM-based NLM algorithm is proposed. We replace the exponential weighted kernel function with a cosine coefficient weighted Gaussian kernel function and incorporate the structural similarity (SSIM) index, which is the state-of-the-art image quality assessment measure, into the NLM image denoising model. Experimental results indicate that the proposed SSIM-based optimal NLM algorithm can get higher PSNR and SSIM, meanwhile, it keeps more detail information and structure feature of the original image and acts out the best visual quality.
ISSN:2161-2927
DOI:10.23919/ChiCC.2017.8028216