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A Comprehensive Approach to Enhance Dark Image Implementing Image Processing Techniques

Overall enhancement for poorly illuminated images is one of the most challenging issues. The degraded images suffer from different aspects of low contrast, color saturation, unnatural noise and non-ideal environment, which are more prominent in dark images. Most image enhancement techniques focus on a specific degradation issue and never lead to the desired enhancement. This paper proposes an efficient dark image enhancement model that addresses essential degradation issues by incorporating gamma correction, gray world, white balance algorithm, denoising and dark channel prior techniques. A Gamma correction technique is implemented to address the low contrast issue of dark images. Accompanying this, we also applied the gray world to balance the colour temperature, Convolution Neural Networks (CNN) to remove the noise and dark channel prior to dehazing. Our experimental results show the outstanding performance of the proposed method in terms of visual and quantitative measures.