Enhancing image quality: A nearest neighbor median filter approach for impulse noise reduction.

Impulse noise is a challenging problem that degrades the quality of an image. In last few decades, Median filtering denoising method has been widely used for impulse noise. Several well-known and efficient algorithms and techniques exist to effectively remove either Gaussian noise or Impulse noise, independently However, in order to remove high noise densities, there has been a shift in the process of filtering methods. New methods adopted are usually computationally expensive. In this paper, Nearest Neighbour median Filter method has been proposed for impulse noise reduction. The proposed method exploited correlation between the pixels of an image. The main objective of proposed approach is detection and reduction of impulse noise in corrupted images without any loss of information. The performance of proposed denoising technique is compared with existing methods on the basis of Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Virtual Information Fidelity (VIF) and computational complexity. From the experimental analysis, it is evident that the proposed denoising method removes impulse noise very effectively, especially at higher noise density levels (more than 70%). Moreover, computational complexity of proposed approach is lesser as compared to state-of-the art methods. Graphical abstract of Nearest Neighbour median Filter [ABSTRACT FROM AUTHOR]