Transform Skip Inspired End-to-End Compression for Screen Content Image

Existing end-to-end image compression mainly concentrates on the coding of natural scene images. However, few works have been dedicated to the end-to-end compression of screen contents. In this paper, we propose an end-to-end compression scheme for screen content images inspired by the ideology of transform skip, with the goal of improving the compression performance for screen content images. In particular, the proposed model takes full consideration of the characteristics of screen contents and involves transform skip branches to the analyses and synthesis process. The transform skip branch equips with coarse feature extraction and reconstruction. As such, the visual signals could be more briefly interpreted at the encoder-side and recovered at the decoder-side. Experimental results show that the proposed method outperforms the existing hyperprior-based model for screen content compression, achieving 10.16% BD-Rate savings in high bit-rate coding scenario and 5.38% BD-Rate savings in low bit-rate coding scenario.