Deep learning-based Edge-aware pre and post-processing methods for JPEG compressed images. (arXiv:2104.04926v2 [eess.IV] UPDATED)

We propose a learning-based compression scheme that envelopes a standard
codec between pre and post-processing deep CNNs. Specifically, we demonstrate
improvements over prior approaches utilizing a compression-decompression
network by introducing: (a) an edge-aware loss function to prevent blurring
that is commonly occurred in prior works & (b) a super-resolution convolutional
neural network (CNN) for post-processing along with a corresponding
pre-processing network for improved rate-distortion performance in the low rate
regime. The algorithm is assessed on a variety of datasets varying …

arxiv cnns codec compression deep learning edge function images loss network post-processing prior processing standard