1. INTRODUCTION
In this paper, we introduce the human visual system based multi-histogram equalization method. This algorithm capitalizes on the advantages of multi-histogram equalization with the benefit of an effective quantitative measure to ensure optimal results as well as local histogram equalization while removing useless information to avoid the production of artifacts. We compare the results of the proposed algorithm against the results of the leading adaptive and local algorithms on a large number of images, presenting a representative collection. This demonstrates the effectiveness of the human vision based multi-histogram equalization algorithm.