Improvement of Denoising in Images Using Generic Image Denoising Network (GID Net)

Images are generated in various forms in different sectors. These images are difficult to handle with and thus, cannot be effectively used in various fields. In this paper, two important techniques in the fields of Image Reconstruction and Restoration are carried out. Image Denoising is the process in which an image is reconstructed from the noisy image. In this process, To restore the original image, the undesired noise is removed. In other words, original (unidentified ) signal, i.e., the image is estimated from the available noisy data. There are many traditional methods of Image Processing which have been used for the process of image denoising [1]. But, these methods are not so robust to handle any type of noise signal which results in a deformed reconstructed denoised image. Therefore, in this paper, a method of image denoising using Image Reconstruction technique is proposed. For this purpose, Deep Learning techniques and architectures have been proposed in order to get the reconstructed denoised image in our paper.