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Proceedings Paper

Decision trees for denoising in H.264/AVC video sequences
Author(s): G. Huchet; J.-Y. Chouinard; D. Wang; A. Vincent
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Paper Abstract

All existing video coding standards are based on block-wise motion compensation and block-wise DCT. At high levels of quantization, block-wise motion compensation and transform produces blocking artifacts in the decoded video, a form of distortion to which the human visual system is very sensitive. The latest video coding standard, H.264/AVC, introduces a deblocking filter to reduce the blocking artifacts. However, there is still visible distortion after the filtering when compared to the original video. In this paper, we propose a non-conventional filter to further reduce the distortion and to improve the decoded picture quality. Different from conventional filters, the proposed filter is based on a machine learning algorithm (decision tree). The decision trees are used to classify the filter's inputs and select the best filter coeffcients for the inputs. Experimental results with 4 × 4 DCT indicate that using the filter holds promise in improving the quality of H.264/AVC video sequences.

Paper Details

Date Published: 28 January 2008
PDF: 8 pages
Proc. SPIE 6822, Visual Communications and Image Processing 2008, 68220Y (28 January 2008); doi: 10.1117/12.766406
Show Author Affiliations
G. Huchet, Laval Univ. (Canada)
J.-Y. Chouinard, Laval Univ. (Canada)
D. Wang, Communications Research Ctr. Canada (Canada)
A. Vincent, Communications Research Ctr. Canada (Canada)


Published in SPIE Proceedings Vol. 6822:
Visual Communications and Image Processing 2008
William A. Pearlman; John W. Woods; Ligang Lu, Editor(s)

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