Description

In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. This uses the Gaussian mixture model to model the image gray-level distribution and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equalized image is generated by transforming the pixels’ gray levels in each input interval to the appropriate output gray-level interval according to the dominant Gaussian component and the cumulative distribution function of the input interval.