Analysis and selection of the methods for fruit image denoise

Jiangsheng Gui; Benxue Ma; Xiuqin Rao; Yibin Ying

doi:10.1117/12.735194

12 October 2007 Analysis and selection of the methods for fruit image denoise

Jiangsheng Gui, Benxue Ma, Xiuqin Rao, Yibin Ying

Proceedings Volume 6761, Optics for Natural Resources, Agriculture, and Foods II; 676117 (2007) https://doi.org/10.1117/12.735194
Event: Optics East, 2007, Boston, MA, United States

Abstract

Applications of machine vision in automated inspection and sorting of fruits have been widely studied by scientists and. Preprocess of the fruit image is needed when it contain much noise. There are many methods for image denoise in literatures and can acquire some nice results, but which will be selected from these methods is a trouble problem. In this research, total variation (TV) and shock filter with diffusion function were introduced, and together with other 6 common used denoise method s for different type noise type were tested. The result demonstrated that when the noise type was Gaussian or random, and SNR of original image was over 8,TV method can achieve the best resume result, when the SNR of original image was under 8, Winner filter can get the best resume result; when the noise type was salt pepper, median filter can achieve the best resume result

Citation Download Citation

Jiangsheng Gui, Benxue Ma, Xiuqin Rao, and Yibin Ying "Analysis and selection of the methods for fruit image denoise", Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 676117 (12 October 2007); https://doi.org/10.1117/12.735194

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