A non-iterative adaptive median filter for image denoising
Vikrant Bhateja, Kartikeya Rastogi, Aviral Verma, Chirag Malhotra · 2014
In this paper, a non-iterative adaptive median filter is proposed for denoising images contaminated with impulse noise. The proposed denoising scheme operates in two steps. Firstly, the pixels are segregated as `noisy' and `noise-free' so that the subsequent processing can be carried out only for the noisy pixels only in the next step. Secondly, the identified noisy pixels are replaced by the median value or by its neighboring pixel value. The term `adaptive' justifies the filters' capability to increase the size of the spatial window, depending upon the decisions made based on statistical parameters (estimated within the local window). Further, the `non-iterative' feature projects that there is no need of recursive filtering to reduce the residual noise content. The proposed denoising method is tested on images with different characteristics and is found to produce better results in terms of the qualitative and quantitative measures of the image in comparison to other filtering approaches.