Detailed image structures and visual textures (of stochastic nature) in digital video are difficult to compress efficiently. At medium to low bit rates, texture flattening and blocking artifacts appear, even when using advanced video coding standards such as H.264/MPEG-4 AVC. In this paper, we propose video compression systems to compress stochastic textures by exploiting rank-reduction techniques. In this work, rank reduction is implemented by applying a singular value decomposition and selective transmission of the primary signal components as in principal component analysis. In the low bit-rate range, our implementation shows encouraging results compared to H.264/MPEG-4 AVC, not only in rate-distortion performance, but also in the improved visual quality of the reconstructed videos.

Date Published: 19 January 2009
PDF: 12 pages
Proc. SPIE 7257, Visual Communications and Image Processing 2009, 725707 (19 January 2009); doi: 10.1117/12.806102

Published in SPIE Proceedings Vol. 7257:
Visual Communications and Image Processing 2009
Majid Rabbani; Robert L. Stevenson, Editor(s)