Paper
4 March 2015 Predicting chroma from luma with frequency domain intra prediction
Nathan E. Egge, Jean-Marc Valin
Author Affiliations +
Proceedings Volume 9410, Visual Information Processing and Communication VI; 941008 (2015) https://doi.org/10.1117/12.2080837
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
This paper describes a technique for performing intra prediction of the chroma planes based on the reconstructed luma plane in the frequency domain. This prediction exploits the fact that while RGB to YUV color conversion has the property that it decorrelates the color planes globally across an image, there is still some correlation locally at the block level.1 Previous proposals compute a linear model of the spatial relationship between the luma plane (Y) and the two chroma planes (U and V).2 In codecs that use lapped transforms this is not possible since transform support extends across the block boundaries3 and thus neighboring blocks are unavailable during intra- prediction. We design a frequency domain intra predictor for chroma that exploits the same local correlation with lower complexity than the spatial predictor and which works with lapped transforms. We then describe a low- complexity algorithm that directly uses luma coefficients as a chroma predictor based on gain-shape quantization and band partitioning. An experiment is performed that compares these two techniques inside the experimental Daala video codec and shows the lower complexity algorithm to be a better chroma predictor.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nathan E. Egge and Jean-Marc Valin "Predicting chroma from luma with frequency domain intra prediction", Proc. SPIE 9410, Visual Information Processing and Communication VI, 941008 (4 March 2015); https://doi.org/10.1117/12.2080837
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CITATIONS
Cited by 7 scholarly publications and 2 patents.
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KEYWORDS
Quantization

Transform theory

Video

Image compression

Computer programming

Lithium

RGB color model

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