Combination of adaptive vector median filter and weighted mean filter for removal of high‐density impulse noise from colour images. Issue 6 (24th April 2017)

• Record Type: Journal Article
• Authors: Roy, Amarjit; Singha, Joyeeta; Manam, Lalit; Laskar, Rabul Hussain
• Is Part Of: IET image processing. Volume 11:Issue 6(2017)
• Page Start: 352
• Page End: 361
• Publication Date: 2017-04-24
• Subjects: image colour analysis -- adaptive filters -- mean square error methods; adaptive vector median filter -- weighted mean filter -- colour images -- high‐density impulse noise removal -- VMF -- noncausal linear prediction error -- peak signal‐to‐noise ratio -- mean squared error -- structural similarity -- feature similarity index; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2016.0320
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : In this study, a combination of adaptive vector median filter (VMF) and weighted mean filter is proposed for removal of high‐density impulse noise from colour images. In the proposed filtering scheme, the noisy and non‐noisy pixels are classified based on the non‐causal linear prediction error. For a noisy pixel, the adaptive VMF is processed over the pixel where the window size is adapted based on the availability of good pixels. Whereas, a non‐noisy pixel is substituted with the weighted mean of the good pixels of the processing window. The experiments have been carried out on a large database for different classes of images, and the performance is measured in terms of peak signal‐to‐noise ratio, mean squared error, structural similarity and feature similarity index. It is observed from the experiments that the proposed filter outperforms (∼1.5 to 6 dB improvement) some of the existing noise removal techniques not only at low density impulse noise but also at high‐density impulse noise.