KNN Classification Based Nonlinear Noise Delineation in Color Image using Optimized BM3D Filter
Mandar D. Sontakke1, Meghana Kulkarni2

1Mr. Mandar D. Sontakke, Department of PG Studies, Visvesaraya Technological University, Belgaum, Karnataka, India.
2Dr. Meghana Kulkarni, Department of PG Studies, Visvesaraya Technological University, Belgaum, Karnataka, India.

Manuscript received on 02 July 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 August 2019 | PP: 209-213 | Volume-8 Issue-10, August 2019 | Retrieval Number: I7610078919/2019©BEIESP | DOI: 10.35940/ijitee.I7610.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Image enhancement using optimized methods along with optimized filters is need of current era. A novel technique is proposed in this paper, which have KNN based pixels classifications strategy. This classification is used to identify noise level and only noisy pixels are processed using optimized BM3D using particle swarm optimization. The outside group pixels are brought back into group thereby removing the noise. The process is further followed by resolution enhancement and Retinex for dynamic presentation purpose. The experimentation results are also included in the paper which shows optimum performance. 
Keywords:  KNN, PSO, nonlinear noise delineation BM3D, Resolution enhancement, Retinex.
Scope of the Article: Classification