Global model for uneven illumination enhancement of document images

Abstract Exponential growth of low-cost digital imagery is latterly observed. Images acquired under uneven lighting are prone to experience poor visibility, which may severely limit the performance of most computational photography and automatic visual recognition applications. Different from current optimization techniques, we design a novel partial differential equation based model to rectify the variable illumination artifacts. In this study, a large number of document samples capturing uneven illumination and low contrast conditions are tested to compare the effectiveness of the proposed local and nonlocal approaches. The suggested algorithm can be applied in Arabic, Latin and Chinese document images with any type of shade.