Statistical Modeling of Inter-Frame Prediction Error and Its Adaptive Transform

Most video coding standards use the discrete cosine transform, known to be near optimal for original images, to transform prediction errors. Since the statistical characteristics of prediction errors are quite different from those of original images, a more suitable transform for prediction errors h...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems for video technology 2011-04, Vol.21 (4), p.519-523
Main Authors: Leu, Ho June, Kim, Seong-Dae, Kim, Wook-Joong
Format: Article
Language:English
Subjects:
Adaptation model
Adaptive transform
Applied sciences
Circuits
Coding
Coding, codes
Computational modeling
covariance function
Covariance matrix
Discrete cosine transforms
Errors
Exact sciences and technology
Image processing
Information, signal and communications theory
inter-frame prediction error
Mathematical models
Miscellaneous
Optimization
Predictive models
PSNR
rank-one modification
Signal and communications theory
Signal processing
Telecommunications and information theory
Transforms
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Summary:Most video coding standards use the discrete cosine transform, known to be near optimal for original images, to transform prediction errors. Since the statistical characteristics of prediction errors are quite different from those of original images, a more suitable transform for prediction errors has to be devised. In this letter, we introduce a novel statistical model for inter-frame prediction error and propose an adaptive transform based on the model. In addition, in order to reduce the computation time, a fast and efficient algorithm is developed. Experiments on well-known image sequences confirm that our proposed transform can improve the performance of transform coding significantly.
ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2011.2125470