Decoder Side Image Quality Enhancement exploiting Inter-channel Correlation in a 3-stage CNN: Submission to CLIC 2018

Kai Cui, Eckehard Steinbach; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018, pp. 2571-2574

In this paper, we describe our submission to the workshop and challenge on learned image compression (CLIC) hosted at CVPR 2018. Lossy compressed images usually suffer from unpleasant artifacts, especially when the bit-rate is low. In order to improve the image quality without spending extra bit-rate, decoder side quality enhancement becomes necessary. Most approaches focus on spatial information exploration, in which the quality enhancement is usually only performed on the luminance component or the gray-scale images which makes the inter-channel correlation is neglected. Motivated by the characteristics of compressed images, a 3-stage CNN based approach is proposed in this paper, which can exploit most of the inter-channel correlation to enhance the image quality at the decoder side. Both objective and subjective evaluations show the noticeable quality improvements compared to Better Portable Graphics (BPG), the state-of-the-art image codec.