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Illumination Estimation for Nature Preserving low-light image enhancement

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TLDR
In this work, initialilluminance is estimated from structure-aware smoothening of a low-light image using guided filters of variable box sizes and illumination is computered by solving the proposed multi-objective illumination problem.
Abstract
In this paper, we proposed a new low-light image enhancementapproach to overcome the above limitations. Theproposed algorithm is named as Nature Preserving LowlightImage Enhancement (NPLIE). NPLIE estimates initialillumination and performs optimal refinement. The proposedalgorithm computes the reflectance component through anelement-wise division of input image by illumination. The enhanced image is obtained as a product of adjusted illumination and reflectance component. In this work, we estimate initialilluminance from structure-aware smoothening of a low-lightimage using guided filters of variable box sizes. We computerefined illumination by solving the proposed multi-objective

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A Comparative Study of Image Dehazing Algorithms

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A Study on Dark Channel Prior based Image Enhancement Techniques

TL;DR: The limitations of the DCP are discussed and a detailed review on how to overcome the limitations of DCP by improving the calculation of global ambient light and transmission map compared to the standard DCP is given.
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Enhancement and denoising method for low-quality MRI, CT images via the sequence decomposition Retinex model, and haze removal algorithm

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