Title of article
Novel mean-shift based histogram equalization using textured regions
Author/Authors
Lai، نويسنده , , Yu-Ren and Chung، نويسنده , , Kuo-Liang and Chen، نويسنده , , Chyou-Hwa and Lin، نويسنده , , Guei-Yin and Wang، نويسنده , , Chao-Hsin، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2012
Pages
9
From page
2750
To page
2758
Abstract
This paper presents a novel mean-shift based histogram equalization method called the MSHE method. The key insight of the proposed MSHE method is that the basis of histogram equalization could be based on textured regions in an image, while impact of smoother regions should be suppressed. Using a mean-shift based approach, the sets of textured regions in an image are determined by finding regions which have a high density of edge concentration. In addition, a new cost function is presented to balance the image quality and contrast enhancement effect for search termination in the proposed algorithm. Based on three typical test images, experimental results show that our proposed MSHE method is quite competitive with the previous eleven methods, such as the HE, BBHE, DSIHE, POHE, RSWHE, DHE, BPDHE, SRHE, GHE, FHE, and THShap.
Keywords
Cost function , Histogram equalization , Machine Learning , Mean-shift method , Textured regions , Contrast enhancement
Journal title
Expert Systems with Applications
Serial Year
2012
Journal title
Expert Systems with Applications
Record number
2351193
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