Enhancing Image Clarity in Real Time: An Automated Gamma Correction Approach for Dehazing
Uma Biswas, Aurgha Karmakar, Avra Ghosh, Sheli Sinha Chaudhuri · 2023
Haze is a natural occurrence resulting from the scattering of unwanted particles in the atmosphere, leading to issues such as color distortion, decreased contrast, and diminished visual appeal in outdoor images. However, computer vision applications necessitate clear images for effective processing. This study proposes a simple and fast image dehazing technique that reduces time complexity by employing gamma correction with a dark channel prior-based technique. This reduction in time complexity enables real-time application. The proposed method enhances image contrast through automatically adjusts brightness levels using gamma correction method where the gamma value is calculated based on the average pixel value of the gray scale image and contrast modification technique to enhance the image quality to suit the image requirements. Experimental results demonstrate that the proposed method produces higher-quality images compared to existing technologies. The combination of gamma correction and contrast limited Adaptive Histogram Equalization proves to be an effective approach for image enhancement and dehazing tasks, resulting in improved contrast and finer details across various image types. Comparative analysis based on parameters such as SSIM, MSE, PSNR, and Correlation confirms the competitive performance of the proposed method.