Adaptive video contrast enhancement with low noise amplification via local data analysis

Unlike global enhancement methods, the proposed algorithm analyses an image in local areas to take full advantage of the local information, and enhances it in two channels to obtain exact result. Furthermore, the algorithm can restrain noise amplification by virtue of local statistic characteristics analysis. To enhance videos rapidly, the Kullback-Leibler distance between frames is used to characterised its similarity, based on it, enhancement function can be updated selectively. Experimental results show that the resultant images from the proposed algorithm are comparable or better than those from previous state-of-the-art methods. On the other hand, the computational complexity of the proposed method is much lower than the current local-data-based contrast enhancement algorithms.