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This report describes the experimental results obtained using a proposedvariational Retinex algorithm for controlled illumination correction. Twocolour restoration and enhancement schemes of the algorithm are presented fordrastically improved results. The algorithm modifies the reflectance imageusing global and local contrast enhancement approaches and gradually removesthe residual illumination to yield highly pleasing results. The proposedalgorithms are optimized by way of simultaneous perceptual quality metric (PQM)stabilization and entropy maximization for fully automated processing solvingthe problem of determination of stopping time. The usage of the HSI or HSVcolour space ensures a unique solution to the optimization problem unlike inthe RGB space where there is none (forcing manual selection of number ofiteration. The proposed approach preserves and enhances details in both brightand dark regions of underexposed images in addition to eliminating the colourdistortion, over-exposure in bright image regions, halo effect and grey-worldviolations observed in Retinex-based approaches. Extensive experiments indicateconsistent performance as the proposed approach exploits and augments theadvantages of PDE-based formulation, performing illumination correction, colourenhancement correction and restoration, contrast enhancement and noisesuppression. Comparisons shows that the proposed approach surpasses most of theother conventional algorithms found in the literature.

Entropy-guided Retinex anisotropic diffusion algorithm based on partial differential equations (PDE) for illumination correction