Contrast Enhancement of Retinal Images Using Green Plan Masking and Whale Optimization Algorithm

Contrast enhancement is considered as most significant pre-processing technique essential for improving the quality of the medical image to carry out more detailed analysis. Various contrast enhancement technique had been developed utilizing masking and filtering approach to enhance medical image quality. Still, these traditional techniques faces challenges in attaining better quality due to presence of fixed scale value. To achive better quality medical image the current research aims on designing efficient contrast technique using Whale Optimization Algorithm (WOA) employed Green Plan Masking (GPM) for application in retinal images. In this proposed work initially the green plan is separted from the input retinal image. then, median filter is applied to the green plan. Following that optimal scale value selection is done using WOA algorithm. Finally, green plan masking approach is applied to obtain enhanced image. Within green plan masking approach the output obtained after applying median filtering is considered. To this output image Gaussian blur and convolutional filter is applied to obtain unsharp green plane image. Further in selection of optimal scale value the edges of the unshrap image is detected using canny edge detection technique. Fitness function considered for WOA algorithm is PNSR of orginal iamge and edge detected image. The remaining red and blue plane is added along with green plane to reach the final enhanced image. Performance of the proposed contrast enhancement technique is analysed through estimating some of the metrics, such as Structural Similarity Index (SSIM), Mean Absolute Error (MAE), Peak Signal to Noise Ratio (PSNR), and Mean Square Error (MSE). The MSE, PSNR, MAE and SSIM value obtained for the proposed design is 0.139, 65.81, 0.039 and 0.97. this analysis suggests that superior performance is attained using this proposed contrast enhancement technique.