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An efficient technique has been proposed for de-noising the image that has greatly sorted the problem caused by the Random Value Impulse Noise (RVIN) in digital gray scale images. The proposed method consists of mainly two main phases: First phase detected the noise pixels using block wise dual threshold method. In the first phase, the boundary pixel has also been processed using interpolation techniques. The output image from the first phased is again processed to refine the corrupted pixels. The correct estimation of the original pixels at the place of corrupted pixels is done by Principal Component Analysis (PCA). Experimental results show the method has an outstanding performance than other state-of-the art the RVIN de-noising methods.
[1] Neeraj Vishwakarma, Shivank Kumar Soni, Chetan Agrawal, “Image De-noising using PCA based Fusion and Neighbor Pixels Interpolation,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2018.7562
