MOTION ESTIMATION AND COMPENSATION BASED ON ALMOST SHIFT-INVARIANT WAVELET TRANSFORM FOR IMAGE SEQUENCE CODING

There has been rapid progress in the application of wavelet transforms to image and image sequence compression. The standard discrete wavele t transform lacks translation invariance in image decomposition which will affect the accuracy of motion estimation from the decomposed subi mages in video coding. In this article, we present a study of applying an almost shift-invariant wavelet transform with ''oversampled frames '' to image sequence compression. With minimal oversampling and biorth ogonal spline wavelets in the almost shift-invariant wavelet transform , motion vectors can be more accurately estimated, contributing toward fewer prediction errors in comparison to those obtained with the stan dard discrete wavelet transform. Thus, an improved compression ratio c an be obtained. We present two new algorithms, the full-motion oversam pling algorithm (FMOS) and the reduced search multiresolution motion e stimation algorithm (MRME), for estimating motion fields at different scales and in different subimages. In the latter, motion vectors at a higher resolution are approximated by the motion vector estimates at a lower resolution through proper scaling. Experiments were performed o n three video sequences with a variety of motions including slow, fast , and zooming. Our results have shown that both algorithms, FMOS and M RME, using the almost shift-invariant oversampled frame wavelet transf orm have reduced prediction errors and enhanced the compression perfor mance in terms of peak-signal-to-noise ratio (PSNR) for the same bit r ate when compared to the existing full motion standard algorithm. (C) 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 214-229, 1 998.