Image denoising using a combined criterion
Evgeny A. Semenishchev, В. И. Марчук, Igor Shrafel, Vadim Dubovskov, Tatyana Onoiko, S. Maslennikov · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
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.