18 January 2010 Improved video coding efficiency exploiting tree-based pixelwise coding dependencies
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Proceedings Volume 7543, Visual Information Processing and Communication; 754303 (2010); doi: 10.1117/12.845571
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States
Abstract
In a conventional hybrid video coding scheme, the choice of encoding parameters (motion vectors, quantization parameters, etc.) is carried out by optimizing frame by frame the output distortion for a given rate budget. While it is well known that motion estimation naturally induces a chain of dependencies among pixels, this is usually not explicitly exploited in the coding process in order to improve overall coding efficiency. Specifically, when considering a group of pictures with an IPPP... structure, each pixel of the first frame can be thought of as the root of a tree whose children are the pixels of the subsequent frames predicted by it. In this work, we demonstrate the advantages of such a representation by showing that, in some situations, the best motion vector is not the one that minimizes the energy of the prediction residual, but the one that produces a better tree structure, e.g., one that can be globally more favorable from a rate-distortion perspective. In this new structure, pixel with a larger descendance are allocated extra rate to produce higher quality predictors. As a proof of concept, we verify this assertion by assigning the quantization parameter in a video sequence in such a way that pixels with a larger number of descendants are coded with a higher quality. In this way we are able to improve RD performance by nearly 1 dB. Our preliminary results suggest that a deeper understanding of the temporal dependencies can potentially lead to substantial gains in coding performance.
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Giuseppe Valenzise, Antonio Ortega, "Improved video coding efficiency exploiting tree-based pixelwise coding dependencies", Proc. SPIE 7543, Visual Information Processing and Communication, 754303 (18 January 2010); doi: 10.1117/12.845571; https://doi.org/10.1117/12.845571
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KEYWORDS
Video

Quantization

Distortion

Video coding

Computer programming

Motion estimation

Motion models

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