Paper Info
Title
Segment dependent dynamic multi-histogram equalization for image contrast enhancement
Abstract
Histogram equalization (HE) method proved to be a simple and most effective technique for contrast enhancement of digital images. However it does not preserve the brightness and natural appearance of the images, which is a major drawback. To overcome this limitation, several Bi- and Multi-HE methods have been proposed. Although the Bi-HE methods significantly enhance the contrast and may preserve the brightness, the natural appearance of the images is not preserved as these methods suffer with the problem of intensity saturation. While Multi-HE methods are proposed to further maintain the brightness and natural appearance of images, but at the cost of contrast enhancement. In this paper, two novel Multi-HE methods for contrast enhancement of natural images, while preserving the brightness and natural appearance of the images, have been proposed. The technique involves decomposing the histogram of an input image into multiple segments based on mean or median values as thresholds. The narrow range segments are identified and are allocated full dynamic range before applying HE to each segment independently. Finally the combined equalized histogram is normalized to avoid the saturation of intensities and un-even distribution of bins. Simulation results show that, for the variety of test images (120 images) the proposed method enhances contrast while preserving brightness and natural appearance and outperforms contemporary methods both qualitatively and quantitatively. The statistical consistency of results has also been verified through ANOVA statistical tool. This work utilizes the concept of histogram equalization.It introduces the new concept of even expansion of histogram bins.More emphasis has been given on avoidance of intensity saturation problem.New full dynamic range allocation of narrow segments has been introduced.New normalization function has also been introduced.
Year
DOI
Venue
2014
10.1016/j.dsp.2013.10.015
Digital Signal Processing
Keywords
Field
DocType
segment dependent dynamic multi-histogram,contrast enhancement,multi-he method,natural appearance,combined equalized histogram,image contrast enhancement,bi-he method,anova statistical tool,novel multi-he method,natural image,histogram equalization
Computer vision,Histogram,Dynamic range,Normalization (statistics),Pattern recognition,Histogram matching,Digital image,Adaptive histogram equalization,Artificial intelligence,Histogram equalization,Brightness,Mathematics
Journal
Volume
Issue
ISSN
25
C
1051-2004
Citations 
PageRank 
References 
9
0.47
23
Authors
3
Name
Order
Citations
PageRank
Mohammad Farhan Khan191.15
E. Khan25612.71
Z. A. Abbasi3181.71