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U. A. Nnolim

In this report, a de-hazing algorithm based on probability and multi-scale fractional order-based fusion is proposed. The proposed scheme improves on a previously implemented multiscale fraction order-based fusion by augmenting its local contrast and edge sharpening features. It also brightens de-hazed images, while avoiding sky region over-enhancement. The results of the proposed algorithm are analyzed and compared with existing methods from the literature and indicate better performance in most cases.

U. A. Nnolim

This report presents the results of a partial differential equation (PDE)-based image enhancement algorithm, for dynamic range compression and illumination correction in the absence of the logarithmic function. The proposed algorithm combines forward and reverse flows in a PDE-based formulation. The experimental results are compared with algorithms from the literature and indicate comparable performance in most cases.

U. A. Nnolim

The experimental results of improved underwater image enhancement algorithms based on partial differential equations (PDEs) are presented in this report. This second work extends the study of previous work and incorporating several improvements into the revised algorithm. Experiments show the evidence of the improvements when compared to previously proposed approaches and other conventional algorithms found in the literature.

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This report describes the experimental results obtained using a proposed variational Retinex algorithm for controlled illumination correction. Two colour restoration and enhancement schemes of the algorithm are presented for drastically improved results. The algorithm modifies the reflectance image using global and local contrast enhancement approaches and gradually removes the residual illumination to yield highly pleasing results. The proposed algorithms are optimized by way of simultaneous perceptual quality metric (PQM) stabilization and entropy maximization for fully automated processing solving the problem of determination of stopping time. The usage of the HSI or HSV colour space ensures a unique solution to the optimization problem unlike in the RGB space where there is none (forcing manual selection of number of iteration. The proposed approach preserves and enhances details in both bright and dark regions of underexposed images in addition to eliminating the colour distortion, over-exposure in bright image regions, halo effect and grey-world violations observed in Retinex-based approaches. Extensive experiments indicate consistent performance as the proposed approach exploits and augments the advantages of PDE-based formulation, performing illumination correction, colour enhancement correction and restoration, contrast enhancement and noise suppression. Comparisons shows that the proposed approach surpasses most of the other conventional algorithms found in the literature.

U. A. Nnolim

This report describes the experimental analysis of proposed underwater image enhancement algorithms based on partial differential equations (PDEs). The algorithms perform simultaneous smoothing and enhancement due to the combination of both processes within the PDE-formulation. The framework enables the incorporation of suitable colour and contrast enhancement algorithms within one unified functional. Additional modification of the formulation includes the combination of the popular Contrast Limited Adaptive Histogram Equalization (CLAHE) with the proposed approach. This modification enables the hybrid algorithm to provide both local enhancement (due to the CLAHE) and global enhancement (due to the proposed contrast term). Additionally, the CLAHE clip limit parameter is computed dynamically in each iteration and used to gauge the amount of local enhancement performed by the CLAHE within the formulation. This enables the algorithm to reduce or prevent the enhancement of noisy artifacts, which if present, are also smoothed out by the anisotropic diffusion term within the PDE formulation. In other words, the modified algorithm combines the strength of the CLAHE, AD and the contrast term while minimizing their weaknesses. Ultimately, the system is optimized using image data metrics for automated enhancement and compromise between visual and quantitative results. Experiments indicate that the proposed algorithms perform a series of functions such as illumination correction, colour enhancement correction and restoration, contrast enhancement and noise suppression. Moreover, the proposed approaches surpass most other conventional algorithms found in the literature.