Reversible interframe compression of medical images: a comparison of decorrelation methods

The authors investigate whether data representing medical image sequences can be compressed more efficiently by taking into account the temporal correlation between the sequence frames. The standard of comparison is intraframe HINT, the best-known reversible decorrelation method for 2-D images. In interframe decorrelation, a distinction is made between extrapolation- and interpolation-based methods, and methods based on local motion estimation, block motion estimation, and unregistered decorrelation. These distinctions give six classes of interframe decorrelation methods, all of which are described. The methods are evaluated by applying them to sequences of coronary X-ray angiograms, ventricle angiograms, and liver scintigrams, as well as to a (nonmedical) videoconferencing image sequence. For the medical image sequences: (1) interpolation-based methods are superior to extrapolation-based methods; (2) estimation of interframe motion is not advantageous for image compression; (3) interframe compression yields entropies comparable to intraframe HINT at higher computational costs; and (4) two methods, unregistered extrapolation and interpolation, are nonetheless possibly interesting alternatives to intraframe HINT.