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The primary objective of enhancement is to improve the contrast an image, that the outcome image is more appropriate than the original image for the given application. One of the simplest, computationally effective and most used empirical algorithms that may improve overall contrast is the class (linear stretching and non-linear stretching) of stretching methods. However, linear and non-linear stretching suffer from several issues, for instance, a low-contrast effect by organizing intensities or an over-brightness effect by super-imposing intensities. The goal of this paper is to present new techniques for image contrast enhancement: (1) a bi-non-linear contrast-stretching algorithm, (2) the optimized combination of linear contrast and non-linear contrast stretching algorithms, and (3) the optimized combination of a linear contrast, a non-linear contrast stretching and a local histogram equalization algorithm. Computer simulations on publicly available Thermal Focus Image Database and the Tufts Face Database show that the proposed methods increase the dynamic image range and demonstrate a significantly improved global and local contrast by taking the most exquisite details and edges. In addition, the simulation results show that the proposed method well correlates with subjective evaluations of image quality. The presented concept is useful in guiding the future design of cutting-edge image enhancement methods.
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