Display devices play image files, of which contrast enhancement methods are usually employed to bring out visual details to achieve better visual quality. However, applied to high resolution images, the contrast enhancement method entails high computation costs mostly due to histogram computations. Therefore, this letter proposes a parallel histogram calculation algorithm using the column histograms and difference histograms to reduce histogram computations. Experimental results show that the proposed algorithm is effective for histogram-based image contrast enhancement.

A histogram is a common graphical descriptor to represent features of distribution of pixels in an image. However, for most of the applications that apply histograms, the time complexity of histogram construction is much higher than that of the other parts of the applications. Hence, column histograms had been presented to construct the local histogram in constant time. In order to increase its performance, this letter proposes a linked-list histogram to avoid generating empty bins, further using hash tables with bin entries to map pixels. Experimental results demonstrate the effectiveness of the proposed method and its superiority to the state-of-the-art method.