Selecting among multiple transform kernels to code prediction residuals is widely used for better compression efficiency. Conventionally, the encoder performs trials of each transform to estimate the rate-distortion (R-D) cost. However, such an exhaustive approach suffers from a significant increase of complexity. In this paper, a novel rate estimation approach is proposed to by-pass the entropy coding process for each transform type using the conditional Laplace distribution model. The proposed method estimates the Laplace distribution parameter by the context inferred by the quantization level and finds the expected rate of the coefficients for transform type selection. Furthermore, a greedy search algorithm for separable transforms is also presented to further accelerate the process. Experimental results show that the transform type selection scheme using the proposed rate estimation method achieves high accuracy and provides a satisfactory speed-performance trade-off.
Google started the WebM Project in 2010 to develop open source, royalty- free video codecs designed specifically for media on the Web. The second generation codec released by the WebM project, VP9, is currently served by YouTube, and enjoys billions of views per day. Realizing the need for even greater compression efficiency to cope with the growing demand for video on the web, the WebM team embarked on an ambitious project to develop a next edition codec AV1, in a consortium of major tech companies called the Alliance for Open Media, that achieves at least a generational improvement in coding efficiency over VP9. In this paper, we focus primarily on new tools in AV1 that improve the prediction of pixel blocks before transforms, quantization and entropy coding are invoked. Specifically, we describe tools and coding modes that improve intra, inter and combined inter-intra prediction. Results are presented on standard test sets.
Google started an opensource project, entitled the WebM Project, in 2010 to develop royaltyfree video codecs for the web. The present generation codec developed in the WebM project called VP9 was finalized in mid2013 and is currently being served extensively by YouTube, resulting in billions of views per day. Even though adoption of VP9 outside Google is still in its infancy, the WebM project has already embarked on an ambitious project to develop a next edition codec VP10 that achieves at least a generational bitrate reduction over the current generation codec VP9. Although the project is still in early stages, a set of new experimental coding tools have already been added to baseline VP9 to achieve modest coding gains over a large enough test set. This paper provides a technical overview of these coding tools.
KEYWORDS: Video coding, Image processing, Signal processing, Quantization, Computer programming, Roads, Visual information processing, Electronic imaging, Current controlled current source, Multilayers
The template matching prediction is an established approach to intra-frame coding that makes use of previously coded pixels in the same frame for reference. It compares the previously reconstructed upper and left boundaries in searching from the reference area the best matched block for prediction, and hence eliminates the need of sending additional information to reproduce the same prediction at decoder. In viewing the image signal as an auto-regressive model, this work is premised on the fact that pixels closer to the known block boundary are better predicted than those far apart. It significantly extends the scope of the template matching approach, which is typically followed by a conventional discrete cosine transform (DCT) for the prediction residuals, by employing an asymmetric discrete sine transform (ADST), whose basis functions vanish at the prediction boundary and reach maximum magnitude at far end, to fully exploit statistics of the residual signals. It was experimentally shown that the proposed scheme provides substantial coding performance gains on top of the conventional template matching method over the baseline.
Google has recently been developing a next generation opensource
video codec called
VP9, as part of the
experimental branch of the libvpx repository included in the WebM project (http://www.webmproject.org/). Starting
from the VP8 video codec released by Google in 2010 as the baseline, a number of enhancements and new tools have
been added to improve the coding efficiency. This paper provides a technical overview of the current status of this
project along with comparisons and other stateoftheart
video codecs H.
264/AVC and HEVC. The new tools that
have been added so far include: larger prediction block sizes up to 64x64, various forms of compound INTER
prediction, more modes for INTRA prediction, ⅛pel
motion vectors and 8tap
switchable subpel interpolation filters,
improved motion reference generation and motion vector coding, improved entropy coding and framelevel
entropy
adaptation for various symbols, improved loop filtering, incorporation of Asymmetric Discrete Sine Transforms and
larger 16x16 and 32x32 DCTs, frame level segmentation to group similar areas together, etc. Other tools and various
bitstream
features are being actively worked on as well. The VP9 bitstream
is expected to be finalized by earlyto
mid2013.
Results show VP9 to be quite competitive in performance with mainstream stateoftheart
codecs.
Conference Committee Involvement (3)
Video Surveillance and Transportation Imaging Applications 2015
10 February 2015 | San Francisco, California, United States
Video Surveillance and Transportation Imaging Applications 2014
3 February 2014 | San Francisco, California, United States
Video Surveillance and Transportation Imaging Applications
4 February 2013 | Burlingame, California, United States
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