Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018) (Matlab)

[WACV 2024 Oral] - ARNIQA: Learning Distortion Manifold for Image Quality Assessment

Quality-Aware Image-Text Alignment for Real-World Image Quality Assessment

🔷 Effects of Degradations on Deep Neural Network Architectures.

Python library for realistically degrading images.

Can we perform face hallucination using limited set of unaligned pairs?

Using an already existing ESRGAN model, degrading our HR images to generate training data for finetuning and further checking the MSE and PSNR for the generated and the original HR images. Link to the original link of Real ESRGAN Repo - https://github.com/xinntao/Real-ESRGAN

A robust learning scheme by proposing a novel augmentation algorithm that scales to emulate a large set of image degradation and occlusion policies

Includes image smoothing, sharpening, and hough transfer.

Digital Image Processing Course | Home Works Design| Fall 2021 | Dr. MohammadReza Mohammadi