Nonlocal Estimation and BM3D Based Face Illumination Normalization
Various lighting conditions for face image seriously affect the accurate rate of face recognition. This paper proposes a kind of nonlocal illumination normalization method, which compares image block mean with the mean of the whole image, gain or punish the upper-left corner pixel values of the image block according to the mean of the image block by using a little gain or punishment factor, use different block size and various gain or punishment factors to remove the illumination by the multi-step iteration; A lot of noise will be generated after the illumination normalization in the original darker area, so using BM3D to denoise images will achieve the ideal final result. The experimental results show that the obtained images are more natural and can better preserve the image details than most existing illumination normalization methods, thus it can achieve higher face recognition rate than the existing methods.
KeywordsNonlocal estimation BM3D Illumination normalization Face recognition
This work was supported by the National Science Foundation of China under grant numbers 61379015; the Natural Science Foundation of Shandong Province under grant number ZR2011FM004; and the Science and Technology Development Project of Taian City under grant number 20113062.
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