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Home / programming language / Online Matlab Projects / Fuzzy Random Impulse Noise Removal From Color Image Sequences
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Fuzzy Random Impulse Noise Removal From Color Image Sequences

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SKU: PROJ3563 Categories: 2015 Projects, Digital Image Processing Projects, Final Year Projects, Online Matlab Projects Tags: academic projects, Android project 2013-2014, Android project Abstract, Android project list, btech projects, dotnet project 2013-2014, dotnet project Abstract, dotnet project list, elysium technologies abstract, elysium technologies chennai, elysium technologies coimbatore, elysium technologies company, elysium technologies courses, elysium technologies erode, elysium technologies inpant traning, elysium technologies internship, elysium technologies jobs, elysium technologies madurai, elysium technologies mou, elysium technologies pondychery, elysium technologies projectlist, elysium technologies projects, elysium technologies ramnad, elysium technologies salem, elysium technologies software, elysium technologies tirunelveli, elysium technologies trichy, Final Year Projects, java projects 2013-2014, java projects Abstract, madurai software company, matlab project 2013-2014, matlab project Abstract, matlab project list, mtech projects, phd research work, Php project 2013-2014, Php project Abstract, Php project list, Power Electronic project 2013-2014, Power Electronic project Abstract, Power Electronic project list, project center Bangalore, project center chennai, project center coimbatore, project center Erode, project center Hyderabad, project center Kollam, project center madurai, project center Pandicherry, project center ramnad, project center Salem, project center Tiruneveli, project center trichy, research center, Students Projects, Vlsi project 2013-2014, Vlsi project Abstract, Vlsi project list
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Fuzzy Random Impulse Noise Removal From Color Image Sequences

Abstract—Fuzzy Random Impulse Noise Removal From Color Image Sequences. In this paper, a new fuzzy filter for the removal of random impulse noise in color video is presented. By working with different successive filtering steps, a very good tradeoff between detail preservation and noise removal is obtained. One strong filtering step that should remove all noise at once would inevitably also remove a considerable amount of detail. Therefore, the noise is filtered step by step. In each step, noisy pixels are detected by the help of fuzzy rules, < Final Year Projects > which are very useful for the processing of human knowledge where linguistic variables are used. Pixels that are detected as noisy are filtered, the others remain unchanged. Filtering of detected pixels is done by blockmatching based on a noise adaptive mean absolute difference. The experiments show that the proposed method outperforms other state-of-the-art filters both visually and in terms of objective quality measures such as the mean absolute error (MAE), the peak-signal-to-noise ratio (PSNR) and the normalized color difference (NCD).

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