ResDeblur-GAN: A ResNet and PatchGAN Based Architecture for Image Deblurring
CH . Jaidev · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · 2025
Abstract—Convolutional deblurring is an advanced image restoration process that aims to recover sharp images from blurred ones caused by motion, defocus, or camera shake. This paper presents a deep learning approach leveraging DeblurGAN- v2, an improved generative adversarial network (GAN) archi- tecture. The model integrates a lightweight generator with a hierarchical discriminator and utilizes attention mechanisms and dense skip connections to retain fine image details. A novel loss function is introduced to balance perceptual, structural similarity, and adversarial components, reducing oversmoothing and enhancing restoration quality. Index Terms—Image Deblurring, Convolutional Neural Net- works, Generative Adversarial Networks, DeblurGAN-v2, Image Restoration, Attention Mechanism, SSIM, PSNR.