Contrast Enhancement of Illumination Layer Image using Optimized Subsection-based Histogram Equalization

doi:10.23940/ijpe.18.11.p8.26242632

Int J Performability Eng ›› 2018, Vol. 14 ›› Issue (11): 2624-2632.doi: 10.23940/ijpe.18.11.p8.26242632

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Contrast Enhancement of Illumination Layer Image using Optimized Subsection-based Histogram Equalization

Yongxin Wang^{a, b, *}, Ming Diao^a, and Haibin Wu^a

^a School of Information and Communication Engineering, Harbin Engineering University, Harbin, 150080, China;
^b The Higher Educational Key Laboratory for Measuring and Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin, 150080, China

Submitted on ;
Contact: * E-mail address: langfei@hrbust.edu.cn
About author:Yongxin Wang received his B.S. and M.S. degrees in Communication Engineering from Harbin University of Science and Technology, Harbin, China, in 2005 and 2010, respectively. His research includes underwater visual target recognition and embedded system design. He is currently a researcher and Ph.D. student at Harbin University of Science and Technology.Ming Diao received his B.S. degree in Electronic Engineering from Harbin Institute of Shipping Engineering, Harbin, China, in 1982. He received his M.S. degree in Communication and Information Systems from Harbin Institute of Shipping Engineering in 1987. His research includes wideband signal detection, processing and recognition, and digital communication. He is currently a professor at Harbin Engineering University.Haibin Wu received his B.S. and M.S. degrees in Instrument Science and Technology from Harbin Institute of Technology, Harbin, China, in 2000 and 2002, respectively, and he received his Ph.D. in Instrument Science and Technology from Harbin University of Science and Technology in 2008. His research includes robotic vision and vision inspection. He is currently a professor at Harbin University of Science and Technology.

Abstract

Abstract: A key problem of underwater image sharpening is to improve image contrast while retaining image detail. The retinex model is used to obtain the illumination and detail layer images. The histogram of the illumination layer image is divided into under-exposure subsection and over-exposure subsection by using the maximum interclass variance method, and the histogram subsections are equalized separately. The above process of histogram dividing and equalization is repeated until the difference between adjacent thresholds for dividing histogram subsections reaches its optimal value. This enhances the contrast of the illumination layer image. As a result, our contrast enhancement method of illumination layer image using optimized histogram subsection based histogram equalization is formed. Furthermore, by multiplying the enhanced contrast of illumination layer image with the original detail layer image, the contrast of underwater image is enhanced and its original details are retained. Some evaluations, e.g. information entropy and mean structure similarity, are examined to show that the underwater image quality is improved appropriately.

Key words: layer image, Retinex model, histogram equalization, contrast enhancement, maximum interclass variance

Yongxin Wang, Ming Diao, and Haibin Wu. Contrast Enhancement of Illumination Layer Image using Optimized Subsection-based Histogram Equalization [J]. Int J Performability Eng, 2018, 14(11): 2624-2632.

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Contrast Enhancement of Illumination Layer Image using Optimized Subsection-based Histogram Equalization

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