MPEG-5 Essential Video Coding Standard is currently being prepared as the video coding standard of ISO/IEC Moving Picture Experts Group. The main goal of the EVC standard development is to provide a significantly improved compression capability over existing video coding standards with timely publication of availability terms. This paper provides an overview of the feature and the characteristics of the MPEG-5 EVC standard.
KEYWORDS: Clouds, Image compression, Computer programming, Principal component analysis, Raster graphics, 3D scanning, Data modeling, Data compression, Neural networks, RGB color model
Recent advances in point cloud capture and applications in VR/AR sparked new interests in the point cloud data
compression. Point Clouds are often organized and compressed with octree based structures. The octree subdivision
sequence is often serialized in a sequence of bytes that are subsequently entropy encoded using range coding, arithmetic
coding or other methods. Such octree based algorithms are efficient only up to a certain level of detail as they have an
exponential run-time in the number of subdivision levels. In addition, the compression efficiency diminishes when the
number of subdivision levels increases. Therefore, in this work we present an alternative enhancement layer to the coarse
octree coded point cloud. In this case, the base layer of the point cloud is coded in known octree based fashion, but the
higher level of details are coded in a different way in an enhancement layer bit-stream. The enhancement layer coding
method takes the distribution of the points into account and projects points to geometric primitives, i.e. planes. It then
stores residuals and applies entropy encoding with a learning based technique. The plane projection method is used for
both geometry compression and color attribute compression. For color coding the method is used to enable efficient raster
scanning of the color attributes on the plane to map them to an image grid. Results show that both improved compression
performance and faster run-times are achieved for geometry and color attribute compression in point clouds.
Conventional video coding techniques make use of the most recently decoded reference frame(s) for motioncompensated
inter prediction. However, it has been shown that to allow using reference frames in a flexible way such
that not only the latest reference frames are used is beneficial. A typical use of flexible reference frame is feedback
based reference picture selection, wherein error-free reference frames available in both the encoder and decoder sides
are selected and used for inter prediction reference. This paper first overviews support of reference picture selection in
different video coding standards, and then presents three specific feedback based reference picture selection methods
using flexible reference frames. In addition, a novel simple reference frame management method that enables using of
flexible reference frame is proposed. The reference frame management method enables much simpler video codec
implementations compared to the complex reference frame management methods in H.263 Annex U and H.264/AVC.
The proposed coding methods and some conventional methods are compared with each other. Simulation results show
significantly improved error resiliency performance of the proposed reference picture selection methods compared to
conventional methods. The effect on the performance imposed by feedback delay variation is also shown. Thanks to the
merits, support of flexible reference frame and the reference frame management has been adopted to the AVS-M video
coding standard.
A modification of block truncation coding (BTC) is proposed in this paper. The modification is with a novel adaptive decimation and interpolation method, and predictive entropy coding of the quantization data. The decimation algorithm is designed based on the directional gradients of image blocks so as (1) to preserve the edge information, (2) to enable the interpolator utilize the already reconstructed data in decoder and (3) to better predict the mean value of a block. The quantization data is not directly coded by the two reconstruction levels, but by the block mean and the difference between the block mean and the lower reconstruction level, to further reduce the bit-rate. Compared to other interpolative methods, the new decimation and interpolation method substantially improves the image quality and removes the annoying blocky artifact at the same time. The proposed scheme, which has low computational complexity, is shown to have comparable or better performance to/than BTC methods combined with vector quantization/discrete cosine transform and the most recently BTC modification that utilize the inter-block correlation.
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