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.
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