Published Paper Details:

Image restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image. Corruption may come in many forms such as motion blur, noise and camera mis-focus. There have a lot of approaches to remove noise from an affected image and to reconstruct a clean image with high visual quality. Some of the non-CNN related approaches are much efficient to remove noise from affected images. But these methods also show some issues like complex optimization, Computational expenses, etc. while performing denoising. To beat the disadvantages of these denoising approaches, CNN related methodologies are created to enhance the denoising performance. These denoising strategies are in acceptable considerations for their efficient performance in image rebuilding. They utilize some techniques like residual learning to enhance the denoising performance. So this paper provides a review on some CNN related image denoising approaches.