Configurable Haze Removal Contrast Dark Channel Priority-Based Contrast Enhancement Model

PROJECT TITLE :

Contrast in Haze Removal Configurable Contrast Enhancement Model Based on Dark Channel Prior

ABSTRACT:

To improve the quality of the rebuilt image, conventional haze removal methods modify the contrast and saturation. The elimination of haze in this method can have an adverse effect on the brightness. Trade-offs between brightness and contrast are necessary to remove haze. Using a luminance reconstruction approach with an energy term, we came up with a new formulation for the haze removal problem. A statistical analysis of haze-free photographs provides the luminance values used to rebuild the image, which allows for higher contrast values than those obtained by other approaches at the same brightness level. The colour constancy method was also used to construct a new module for the estimate of ambient light. When noise is taken into account, this module outperforms other techniques. A one-megapixel image can be processed in 0.55 seconds using the proposed framework. According to our theory of contrast, the proposed haze-removal framework can be used to remove haze from images.

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