Enhancing Image Quality with GAN Super Resolution Evaluation

The present study presents a novel approach to enhance the quality of celebrity photos by utilizing an innovative framework known as Profile SR-GAN. The aim is to increase the resolution of low-quality celebrity photos, so they appear significantly better. In this work, Generative Adversarial Network (GAN) has been applied as it is highly efficient at generating images. Two key performance metrics have been used, PSNR and SSIM, to evaluate the effectiveness of our approach. In comparison to the noise in the original low-quality photographs, PSNR enables us to determine how clear the high-resolution images are. SSIM analyzes brightness, contrast, and general structure to assist us compare the original and upgraded photos. The effectiveness of GAN model has been demonstrated in enhancing the image resolution through our detailed study. This research study has gained a greater knowledge of this technique's effectiveness and its potential uses in many contexts.