Enhancement of Images Using Optimized Gamma Correction with Weighted Distribution Via Differential Evolution Algorithm

Whenever the acquired images having flaws such as poor visual appearance to the eyes, noise, or low quality which degraded the quality of the image. In order to increase the visual appearance, image enhancement should be used. The primary goal of image enhancement is to suppress blemishes in an image while retaining useful information. Many researchers suggested different kinds of enhancement processes that produced positive results. The conventional Histogram Equalization (HE) is a popular technique for refining the quality of a taken image. However, it is possible that unwanted contrast enhancement may occur. As a result, we have an unnatural presence in a processed image, as well as visual objects. To address this, we developed a novel hybrid algorithm called Optimized Gamma Correction with Weighted Distribution (OGCWD), which combines the Differential Evolution algorithm and Adaptive Gamma Correction with Weighted Distribution. The proposed method is an automated transformation process that aids in improving the brightness of a lowered image. The proposed OGCWD algorithm outperforms state-of-the-art image enhancement techniques in terms of structural Similarity Index (SSIM), Mean Square Error (MSE), and Peak Signal to Noise Ratio (PSNR).