AN IMPLEMENTATION OF DEEP LEARNING AND SUPER RESOLUTION IMAGING AFTER IMAGE INPAINTING FOR IMAGE QUALITY ENHANCEMENT

Abstract

The quality of the images can be improved by using different methods to achieve good visualization of the images. In this implementation, the image inpainting technique is used followed by the super resolution image enhancement for the betterment of the images. This can be achieved by applying the Deep learning technique on the images to implement the super resolution enhancement technique after image inpainting to achieve great results. The obtained output image after several processing can be measured for achieved image quality using Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Correlation Coefficient (CC). The Fast Marching method [2]  in the image inpainting is used for this implementation. And also, the MATLAB Software is used for this process. The supervised deep learning is used to achieve the greater quality of the images in this implementation.