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Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images

Publish Year: 1397
Type: Journal paper
Language: English
View: 343

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Document National Code:

JR_JADM-6-1_001

Index date: 10 July 2019

Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images abstract

Histogram Equalization technique is one of the basic methods in image contrast enhancement. Using this method, in the case of images with uniform gray levels (with narrow histogram), causes loss of image detail and the natural look of the image. To overcome this problem and to have a better image contrast enhancement, a new two-step method was proposed. In the first step, the image histogram is partitioned into some sub-histograms according to mean value and standard deviation, which will be controlled with PSNR measure. In the second step, each sub-histogram will be improved separately and locally with traditional histogram equalization. Finally, all sub-histograms will be combined to obtain the enhanced image. Experimental results shows that this method would not only keep the visual details of the histogram, but also enhance image contrast.

Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images Keywords:

Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images authors

M. Shakeri

Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran.

M.H. Dezfoulian

Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran.

H. Khotanlou

Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran.