An Adaptive Histogram Equalization Based Local Technique for Contrast Preserving Image Enhancement
Author(s) -
Joonwhoan Lee,
Suresh Raj Pant,
Hee-Sin Lee
Publication year - 2015
Publication title -
international journal of fuzzy logic and intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.296
H-Index - 9
eISSN - 2093-744X
pISSN - 1598-2645
DOI - 10.5391/ijfis.2015.15.1.35
Subject(s) - adaptive histogram equalization , artificial intelligence , histogram equalization , computer vision , computer science , contrast (vision) , pixel , image (mathematics) , image quality , histogram , edge enhancement , contrast enhancement , image histogram , pattern recognition (psychology) , image enhancement , image processing , image texture , medicine , magnetic resonance imaging , radiology
The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.
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