Open AccessOn the Properties of Some Adaptive Morphological Filters for Salt and Pepper Noise Removal
Author(s) -
Marisol Mares-Javier,
Carlos Guillén-Galván,
Rafael Lemuz López,
Johan Debayle
Publication year - 2021
Publication title -
image analysis and stereology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 27
eISSN - 1854-5165
pISSN - 1580-3139
DOI - 10.5566/ias.2418
Subject(s) - mathematical morphology , salt and pepper noise , grayscale , dilation (metric space) , noise reduction , median filter , noise (video) , filter (signal processing) , artificial intelligence , computer science , mathematics , image processing , computer vision , image (mathematics) , pattern recognition (psychology) , geometry
Mathematical Morphology (MM) is a tool that can be applied to many digital image processing tasks that include the reduction of impulsive or salt and pepper noise in grayscale images. The morphological filters used for this task are filters resulting from two basic operators: erosion and dilation. However, when the level of contamination of the image is higher, these filters tend to distort the image. In this work we propose a pair of operators with properties, that better adapt to impulsive noise than other classical morphological filters, it is demonstrated to be increasing idempotent morphological filters. Furthermore, the proposed pair turns out to be a ∧-filter and a ∨-filter which allow to build morphological openings and closings. Finally, they are compared with other filters of the state-of-the-art such as: SMF, DBAIN, AMF and NAFSM, and have shown a better performance in time-quality ratio when the noise level is above 50%.