Signal-adapted transform coding of sequences

Benoit M. M. Macq; Serge Comes; J. Y. Mertes; Maria Paula Queluz

doi:10.1117/12.157888

22 October 1993 Signal-adapted transform coding of sequences

Benoit M. M. Macq, Serge Comes, J. Y. Mertes, Maria Paula Queluz

Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.157888
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States

Abstract

In standard DCT coding schemes like MPEG, the sequences compression is achieved by motion compensation, transformation, quantization, and entropy coding. In this paper, we have followed the same path by adapting to the image signal the elements of the coding scheme. The motion compensation is achieved by a block-matching method, where the size of the blocks is adapted to the signal. Great attention has been paid to the relevance of the motion field. Combined with the motion compensation, the two fields of each frame are merged, taking into account the measured motion vectors, to compose a pseudo-progressive frame. The encoding is applied to this `motion-compensated progressive' frame. A wavelet decomposition is then applied on each (inter or intra) frame. Such a transform, intrinsically owning linear- phase and perfect reconstruction properties, has been optimized for maximizing a perceptually weighted coding gain. The wavelet coefficients are thereafter vector-quantized, in order to reach the maximum perceptual SNR : frequency weighting is taken into account. The relevance of the measured vector field allows a precise spatio-temporal quantization optimization. The vectors are entropy coded taking into account the remaining inter-band dependence, by an adapted entropy code. Results obtained from 1 Mbit/s to 8 Mbit/s are shown for moving sequences at the conference.

Citation Download Citation

Benoit M. M. Macq, Serge Comes, J. Y. Mertes, and Maria Paula Queluz "Signal-adapted transform coding of sequences", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.157888

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