Histogram modification using grey-level co-occurrence matrix for image contrast enhancement

Histogram modification is an important technique for contrast enhancement. Most changes of histogram are based on global or local region grey-levels information. In this study, a novel grey-level co-occurrence matrix (GCOM)-based histogram equalisation (COHE) method is proposed. A GCOM is a matrix or distribution of co-occurring grey-levels at a given offset, in which each row or column vector is actually a conditional histogram. The procedure of COHE has two steps. First, it is to equalise the modified conditional histograms, which are weighted sums of uniformly distributed histograms and the conditional histograms. An adjusting method of weight parameter is also presented in this study. Conditional histograms equalisations have the advantage of enlarging the difference between given grey-levels and other spatially adjacent grey-levels. Second, COHE algorithm finds mapping to obtain global enhance by weighting all the conditional translated grey-levels with original image histogram. However, it could produce over-enhanced unnatural looking images because of spikes of conditional histogram and original histogram. To deal with this, this study introduces methods of adjusting the conditional histogram and original histogram based on GCOM. Experimental results demonstrate that the proposed method can enhance the images effectively.