High efficient contrast enhancement using parametric approximation

In this study, a local contrast enhancement method, namely Parametric-Oriented Histogram Equalization (POHE), is proposed to effectively yield enhanced results. In general, the grayscale distribution of a specific region in an image can be modeled with a kernel function such as the Gaussian, and thus the corresponding estimated cumulative distribution function (cdf) can be considered as the transformation function for contrast enhancement. The required parameters, however, still need to access all of the pixels in the corresponding region, and thus consume a huge amount of computations. To cope with this, the concept of integral image is adopted to effectively derive the required parameters. In the experimental results, former well-known speed-oriented methods are adopted for comparison, and the results demonstrate that the proposed methods can provide high practical value for biometric and tracking/detection these active issues who desire high efficiency.