Non‐parametric modified histogram equalisation for contrast enhancement. Issue 7 (1st October 2013)

• Record Type: Journal Article
• Authors: Poddar, Shashi; Tewary, Suman; Sharma, Deewakar; Karar, Vinod; Ghosh, Ashish; Pal, Sankar K.
• Is Part Of: IET image processing. Volume 7:Issue 7(2013)
• Page Start: 641
• Page End: 652
• Publication Date: 2013-10-01
• Subjects: equalisers -- image enhancement; degree of entropy unpreservation -- edge‐based contrast measure -- structure similarity index measures -- qualitative assessments -- quantitative assessments -- image brightness -- grey scale -- spatial transformation -- generalised contrast enhancement algorithm -- image enhancement -- nonparametric modified histogram equalisation; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2012.0507
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Histogram equalisation has been a much sought‐after technique for improving the contrast of an image, which however leads to an over enhancement of the image, giving it an unnatural and degraded appearance. In this framework, a generalised contrast enhancement algorithm is proposed which is independent of parameter setting for a given dynamic range of the input image. The algorithm uses the modified histogram for spatial transformation on grey scale to render a better quality image irrespective of the image type. Added to this, two variants of the proposed methodology are presented, one of which preserves the brightness of original image while the other variant increases the image brightness adaptively, giving it a better look. Qualitative and quantitative assessments like degree of entropy un‐preservation, edge‐based contrast measure and structure similarity index measures are then applied to the 500 image data set for comparing the proposed algorithm with several existing state‐of‐the‐art algorithms. Experimental results show that the proposed algorithm produces better or comparable enhanced images than several algorithms.