Title :
Image Contrast Enhancement Using Color and Depth Histograms
Author_Institution :
Dept. of Multimedia Eng., Dongguk Univ., Seoul, South Korea
Abstract :
In this letter, we propose a new global contrast enhancement algorithm using the histograms of 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.
Keywords :
Gaussian processes; image colour analysis; image enhancement; Gaussian mixture model; color histograms; depth image histograms; global contrast enhancement algorithm; histogram-modification framework; local image contrast; mapping curve estimation; position partitioning; spatially neighboring pixels; Color; Genetic algorithms; Histograms; Image color analysis; Labeling; Partitioning algorithms; Signal processing algorithms; Contrast enhancement; depth image; histogram modification; histogram partitioning;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2014.2303157