Adaptive Quantisation in HEVC for Contouring Artefacts Removal in UHD Content

Contouring artefacts affect the visual experience of some particular types of compressed Ultra High Definition (UHD) sequences characterised by smoothly textured areas and gradual transitions in the value of the pixels. This paper proposes a technique to adjust the quantisation process at the encoder so that contouring artefacts are avoided. The devised method does not require any change at the decoder side and introduces a negligible coding rate increment (up to 3.4% for the same objective quality). This result compares favourably with the average 11.2% bit-rate penalty introduced by a method where the quantisation step is reduced in contour-prone areas

Deep motion‐compensation enhancement in video compression

This work introduces the multiframe motion-compensation enhancement network (MMCE-Net), a deep-learning tool aimed at improving the performance of current video coding standards based on motion-compensation, such as H.265/HEVC. The proposed method improves the inter-prediction coding efficiency by enhancing the accuracy of the motion-compensated frame and thereby improving the rate-distortion performance. MMCE-Net is a neural network that jointly exploits the predicted coding unit and two co-located coding units from previous reference frames to improve the estimation of the temporal evolution of the scene. This letter describes the architecture of MMCE-Net, how it is integrated into H.265/HEVC and the corresponding performance

THE OPEN-SOURCE TURING CODEC: TOWARDS FAST, FLEXIBLE AND PARALLEL HEVC ENCODING

The Turing codec is an open-source software codec compliant with the HEVC standard and specifically designed for speed, flexibility, parallelisation and high coding efficiency. The Turing codec was designed starting from a completely novel backbone to comply with the Main and Main10 profiles of HEVC, and has many desirable features for practical codecs such as very low memory consumption, advanced parallelisation schemes and fast encoding algorithms. This paper presents a technical description of the Turing codec as well as a comparison of its performance with other similar encoders. The codec is capable of cutting the encoding complexity by an average 87% with respect to the HEVC reference implementation for an average coding penalty of 11% higher rates in compression efficiency at the same peak-signal-noise-ratio level