Adaptive probability filter for removing salt and pepper noises. Issue 6 (1st June 2018)

• Record Type: Journal Article
• Authors: Chen, Jiayi; Zhan, Yinwei; Cao, Huiying; Wu, Xingda
• Is Part Of: IET image processing. Volume 12:Issue 6(2018)
• Page Start: 863
• Page End: 871
• Publication Date: 2018-06-01
• Subjects: image denoising -- object detection -- adaptive filters -- image enhancement -- image resolution -- statistical analysis -- probability; adaptive probability filter -- salt‐and‐pepper noises removal -- salt‐and‐pepper noises detection -- minimum intensity values -- maximum intensity values -- noise distribution -- noise‐free intensities -- repeated frequency -- statistical significance -- noise‐free pixels -- peak‐signal‐to‐noise ratio -- image enhancement factor -- visual representation -- noise densities; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.0910
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : To overcome the drawbacks of existing filters for salt and pepper noises, an adaptive probability filter is proposed. For an image, it detects salt and pepper noises based on the characteristic of minimum and maximum intensity values of the images, as well as the distribution of noise. If the noise‐free intensities in neighbourhood repeat with a certain probability, the noise‐free intensity with highest repeated frequency is used to remove noise based on the statistical significance; otherwise, the median of noise‐free pixels in neighbourhood is used to remove noise. Experiments show that the proposed method is capable of detecting noise more accurately and perform much better than the existing distinguished filters in terms of peak‐signal‐to‐noise ratio, image enhancement factor, and visual representation at all the noise densities.