Open AccessFiltering of mixed Gaussian and impulsive noise using morphological contrast detectors
Author(s) -
MendiolaSantibañez Jorge D.,
TerolVillalobos Iván R.
Publication year - 2014
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.2012.0615
Subject(s) - contrast (vision) , gaussian noise , detector , noise (video) , gaussian , computer science , artificial intelligence , pattern recognition (psychology) , mathematics , algorithm , physics , image (mathematics) , telecommunications , quantum mechanics
Several morphological transformations to detect noise are introduced. The initial method is a modification of a procedure presented previously in the current literature. The proposals given in the study allow to detect noise in two ways: (i) using a contrast measure and (ii) applying different proximity criteria into several proposed toggle mappings. In the end, two of the proposals given in this study yield a better performance with respect to methods in which this research is based. However, although the methodology to identify noise works adequately, the results are limited due to the use of the structuring element. In Section 4, an image with two types of noise is cleaned. Such image is contaminated with zero mean Gaussian noise with 0.01 variance and 5% of salt and pepper noise. From this experiment, the proposal giving the best performance is selected; subsequently, this is compared with other recent operators as PDEs, wavelets, morphological connected rank max opening and amoebas.