Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images
محل انتشار: مجله هوش مصنوعی و داده کاوی، دوره: 6، شماره: 1
سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 319
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شناسه ملی سند علمی:
JR_JADM-6-1_001
تاریخ نمایه سازی: 19 تیر 1398
چکیده مقاله:
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.
کلیدواژه ها:
نویسندگان
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.