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

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Bibliographic Details
Title:	Contrast Enhancement of Illumination Layer Image using Optimized Subsection-based Histogram Equalization.
Authors:	Yongxin Wang^1,2 langfei@hrbust.edu.cn, Ming Diao¹, Haibin Wu¹
Source:	International Journal of Performability Engineering. Nov2018, Vol. 14 Issue 11, p2624-2632. 9p.
Subjects:	Underwater imaging systems, Optical oceanography, Lighting, Image quality analysis, Histograms
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. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
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. [ABSTRACT FROM AUTHOR]
ISSN:	09731318
DOI:	10.23940/ijpe.18.11.p8.26242632