Histogram equalization and optimal profile compression based approach for colour image enhancement

Many vision based applications depend on images with sufficiently high contrast and colourfulness so that ample amount of information is available to accurately describe objects captured in an image scene. Poor image capturing conditions are often unavoidable but can be compensated. Approaches based on intensity histogram equalization are popular to increase the information content within an image but over-enhancement often results in the production of unwanted artefacts. Furthermore, when constrained to only an intensity-based enhancement, insufficient enrichment on colourfulness and saturation is often observed. In order to address these limitations concurrently, a pipelined approach that incorporates a colour channel stretching process, a histogram equalization step, a magnitude compression procedure, and a saturation maximization stage is proposed. Quantitative and qualitative results obtained from experiments on a wide variety of natural scene images demonstrate the effectiveness of the proposed approach over other methods at reducing artefact while increasing image contrast and colourfulness.