Real-time Restoration of Quality Distortions in Mobile Images using Deep Learning
Taşkın Koçak, Cagkan Ciloglu · 2020
Frames provided by camera on mobile devices may be distorted because of camera defects and/or weather conditions such as rain and snow. These distortions affect image classifiers. This paper proposes using deep-learning architectures to restore quality distortions in real-time mobile video for image classifiers. An iOS based app is developed using CoreML to show that deep convolutional auto-encoder (CAE) based methods can be used to restore picture quality.