Paper
19 May 2016 Image denoising using a combined criterion
Evgeny Semenishchev, Vladimir Marchuk, Igor Shrafel, Vadim Dubovskov, Tatyana Onoyko, Stansilav Maslennikov
Author Affiliations +
Abstract
A new image denoising method is proposed in this paper. We are considering an optimization problem with a linear objective function based on two criteria, namely, L2 norm and the first order square difference. This method is a parametric, so by a choice of the parameters we can adapt a proposed criteria of the objective function. The denoising algorithm consists of the following steps: 1) multiple denoising estimates are found on local areas of the image; 2) image edges are determined; 3) parameters of the method are fixed and denoised estimates of the local area are found; 4) local window is moved to the next position (local windows are overlapping) in order to produce the final estimate. A proper choice of parameters of the introduced method is discussed. A comparative analysis of a new denoising method with existed ones is performed on a set of test images.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Evgeny Semenishchev, Vladimir Marchuk, Igor Shrafel, Vadim Dubovskov, Tatyana Onoyko, and Stansilav Maslennikov "Image denoising using a combined criterion", Proc. SPIE 9869, Mobile Multimedia/Image Processing, Security, and Applications 2016, 98690E (19 May 2016); https://doi.org/10.1117/12.2223610
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KEYWORDS
Denoising

Image denoising

Image compression

Signal processing

Interference (communication)

Digital imaging

Image acquisition

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