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Improved NL-means Algorithm for Two-dimensional Gel Electrophoresis Images Denoising

Denoising is a fundamental stage of two-dimensional gel electrophoresis (2DGE) images analysis, which strongly influences spot detection, spot matching and other pixel-based methods. It is critical to effective noise suppression. This paper proposed a new method based on the Non-Local-means (NLmeans) algorithm, which is simple and can protect the structure well. Compared with the Translation Invariant Wavelet Transform (TIWT), the Total Variation (TV) and the NL-means, the performance of the improved NL-means algorithm outperforms them in PSNR values and the visual quality of the image. Experiments also verified that the improved NL-means algorithm is a more suitable method for 2DGE images denoising.