Parametric-oriented fitting for local contrast enhancement

Local image contrast enhancement methods extract more informative details comparing with the global methods. Yet, the traditional schemes require to access all of the pixels in a local region to obtain the cumulative distribution function (cdf) for further enhancement, i.e., adaptive histogram equalization (AHE), and thus the time complexity drastically increases accordingly when the block size increases. Consequently, some speed-up ingenuities such as block-wise strategy and simple proportionally averaging manner are employed to cope with this issue, yet serious blocking artifact or low contrast issues are accompanied. In this study, a local enhancement method, namely corrected parametric-oriented histogram equalization (CPOHE), is proposed to effectively yield enhanced results with high contrast and artifact-free texture using the concept of integral image, and further correct the accompanied distortion. As documented in the experimental results, the proposed method provides a high practical value for applied in visual perception, biometric, and tracking/detection applications.