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Motion modelling plays a central role in video compression. This role is even more critical in highly textured video sequences, whereby a small error can produce large residuals that are costly to compress. While the translational motion model employed by existing coding standards, such as HEVC, is sufficient in most cases, using higher order models is beneficial; for this reason, the upcoming video coding standard, VVC, employs a 4-parameter affine model.

This paper describes the block coding algorithm that underpins the new High Throughput JPEG 2000 (HTJ2K) standard. The objective of HTJ2K is to overcome the computational complexity of the original block coding algorithm, by providing a drop-in replacement that preserves as much of the JPEG 2000 feature set as possible, while allowing reversible transcoding to/from the original format. We show how the new standard achieves these goals, with high coding efficiency, and extremely high throughput in software.

Intra interpolation filters for intra angular prediction play an important role in the coding performance. In the intra angular prediction of VVC, which is being standardized by the joint video coding expert team (JVET), block-size based switchable interpolation filters between 4-tap cubic and Gaussian interpolation filters is being studied. Although the two filters have different frequency characteristics, block size-based criteria are insufficient to represent the reference sample characteristics.

This paper deals with the current trends of new compression methods for 3D point cloud contents required to ensure efficient transmission and storage.
The representation of 3D point clouds geometry remains a challenging problem, since this signal is unstructured.
In this paper, we introduce a new hierarchical geometry representation based on adaptive Tree-Structured Point-Lattice Vector Quantization (TSPLVQ).
This representation enables hierarchically structured 3D content that improves the compression performance for static point clouds.

This paper presents a novel method for a data-driven training of
affine-linear predictors which perform intra prediction in state-ofthe-
art video coding. The main aspect of our training design is the
use of subband decomposition of both the input and the output of the
prediction. Due to this architecture, the same set of predictors can be
shared across different block shapes leading to a very limited memory
requirement. Also, the computational complexity of the resulting
predictors can be limited such that it does not exceed the complexity

This paper presents an efficient method for encoding common projection formats in 360◦ video coding, in which we exploit inactive regions. These regions are ignored in the reconstruction of the equirectangular format or the viewport in virtual reality applications. As the content of these pixels is irrelevant, we neglect the corresponding pixel values in ratedistortion optimization, residual transformation, as well as inloop filtering and achieve bitrate savings of up to 10%.

High-dynamic-range (HDR) video streams have been delivered through high-efficiency video coding (HEVC). HDR video tone mapping is required additionally but is operated separately to adjust the content’s dynamic range for each display device. HDR video tone mapping and HEVC encoding share common computational processes for spatial and temporal coherence in a video stream; however, they have been developed and implemented independently with their own computational budgets.