Open AccessAdaptive probability filter for removing salt and pepper noises
Author(s) -
Chen Jiayi,
Zhan Yinwei,
Cao Huiying,
Wu Xingda
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0910
Subject(s) - salt and pepper noise , value noise , median filter , noise (video) , gradient noise , computer science , artificial intelligence , mathematics , noise spectral density , filter (signal processing) , gaussian noise , noise measurement , neighbourhood (mathematics) , image noise , pattern recognition (psychology) , computer vision , noise floor , statistics , noise reduction , image (mathematics) , noise figure , image processing , telecommunications , amplifier , mathematical analysis , bandwidth (computing)
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.