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Proceedings Paper

Vector clustering in symmetry-folded spaces for image vector quantization
Author(s): Fabio Lavagetto
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Paper Abstract

A significant amount of residual redundancy in vector quantized images can be further reduced by taking into accounts symmetries such as those presented by rotated or flipped versions of the same vector. Decorrelating data blocks with respect to this kind of symmetry allows for more efficient vector clustering, thus increasing the compression performances of the coder. In this paper an innovative though intuitively simple technique is presented for image vector quantization operating on a symmetry folded space. The symmetry invariance of the vector space is obtained by rotating and flipping each block in order to minimize a suitable functional: by means of this normalization procedures, rotated or flipped versions of the same block are mapped onto the same point in the folded space, thus clustering together previously scattered vectors. Fewer bits are therefore needed to quantize the redistributed vectors without increasing the level of distortion or, conversely, a lower distortion is achieved with unchanged bit rate. In order to invert the normalization procedure, some side information must be delivered to the decoder to drive the inverse operations of block rotation and flipping. However, because of the high level of spatial redundancy, this inverse operation can be efficiently predicted by analyzing nearby blocks. Only the prediction error is therefore coded and sent as side information. Experimental results have shown that for many image classes the entropy of the prediction error is fairly small in comparison with the bit saving stemming from the reduced size of the vectors and of the reconstruction look-up table.

Paper Details

Date Published: 1 November 1992
PDF: 8 pages
Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); doi: 10.1117/12.131463
Show Author Affiliations
Fabio Lavagetto, Univ. di Genova (Italy)

Published in SPIE Proceedings Vol. 1818:
Visual Communications and Image Processing '92
Petros Maragos, Editor(s)

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