Local Contrast Enhancement Utilizing Bidirectional Switching Equalization of Separated and Clipped Subhistograms
Author(s) -
Haidi Ibrahim,
Seng Chun Hoo
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/848615
Subject(s) - histogram equalization , adaptive histogram equalization , contrast (vision) , equalization (audio) , histogram , histogram matching , artificial intelligence , brightness , computer science , benchmark (surveying) , color normalization , computer vision , pattern recognition (psychology) , image (mathematics) , mathematics , image processing , color image , algorithm , geography , decoding methods , physics , geodesy , optics
Digital image contrast enhancement methods that are based on histogram equalization technique are still useful for the use in consumer electronic products due to their simple implementation. However, almost all the suggested enhancement methods are using global processing technique, which does not emphasize local contents. Therefore, this paper proposes a new local image contrast enhancement method, based on histogram equalization technique, which not only enhances the contrast, but also increases the sharpness of the image. Besides, this method is also able to preserve the mean brightness of the image. In order to limit the noise amplification, this newly proposed method utilizes local mean-separation, and clipped histogram bins methodologies. Based on nine test color images and the benchmark with other three histogram equalization based methods, the proposed technique shows the best overall performance.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom