Implementation and Analysis of Image Contrast Enhancement using Gaussian Mixture Model
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2015, Vol 4, Issue 7
Abstract
In this paper, we propose a new global contrast enhancement algorithm using the histogram color and depth images. On the basis of the histogram-modification framework, the color and depth image histograms are first partitioned into sub- intervals using the Gaussian mixture model. The positions partitioning the color histogram are then adjusted such that spatially neighboring pixels with the similar intensity and depth values can be grouped into the same sub-interval. By estimating the mapping curve of the contrast enhancement for each sub-interval, the global image contrast can be improved without over-enhancing the local image contrast. Experimental results demonstrate the effectiveness of the proposed algorithm. The current major project in contrast enhancement is to partition the input histogram into multiple sub histograms before final equalization of each sub-histogram is performed. This paper presents a novel contrast enhancement method based on Gaussian mixture modeling of image histograms, which provides a sound theoretical underpinning of the partitioning process .By estimating the mapping curve of the contrast enhancement for each sub-interval, the global image contrast can be improved without over-enhancing the local image contrast.
Authors and Affiliations
K. Swetha, V. Prasad
Keywords
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