Publication: Filter optimization and complexity reduction for video coding using graph-based transforms
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2013
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IEEE
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Abstract
The basis functions of lifting transform on graphs are completely
determined by finding a bipartition of the graph and defining the
prediction and update filters to be used. In this work we consider the
design of prediction filters that minimize the quadratic prediction error
and therefore the energy of the detail coefficients, which will give
rise to higher energy compaction. Then, to determine the graph bipartition,
we propose a distributed maximum-cut algorithm that significantly
reduces the computational cost with respect to the centralized
version used in our previous work. The proposed techniques
show improvements in coding performance and computational cost
as compared to our previous work.
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Keywords
Wavelet transforms, Video coding, MCTF, Lifting, Graphs
Bibliographic citation
Proceedings of 20th IEEE International Conference on Image Processing (ICIP). September 15-18, 2013. Melbourne, Australia. IEEE, pp. 1948-1952