Image Denoising and Super-Resolution using Residual Learning of Deep Convolutional Network

Understand

Image super-resolution and denoising are two important tasks in image processing that can lead to improvement in image quality.

• Image super-resolution is the task of mapping a low resolution image to a high resolution image whereas denoising is the task of learning a clean image from a noisy input.
• We propose and train a single deep learning network that we term as SuRDCNN (super-resolution and denoising convolutional neural network), to perform these two tasks simultaneously .
• Our model nearly replicates the architecture of existing state-of-the-art deep learning models for super-resolution and denoising.