Publication Details
Tim Bruylants, Alin Alecu, T. Kimpe, Adrian Munteanu, Peter Schelkens

SPIE Medical Imaging 2007: Image Processing

Contribution To Book Anthology


The JPEG2000 standard is currently widely adopted in medical and volumetric data compression. In this respect, a 3D extension (JPEG2000 Part 10 - JP3D) is currently being standardized. However, no suitable 3D context model is yet available within the standard, such that the context-based arithmetic entropy coder of JP3D still uses the 2D context model of JPEG2000 Part 1. In this paper, we propose a context design algorithm that, based on a training set, generates an optimized 3D context model, while avoiding an exhaustive search and at the same time keeping the space and time complexities well within the limits of today hardware. The algorithm comes as a solution for the situations in which the number of allowable initial contexts is very large. In this sense, the three-dimensional 3x3x3 context neighborhood investigated in this paper is a good example of an instantiation that would have otherwise been computationally unfeasible. Furthermore, we have designed a new 3D context model for JP3D. We show that the JP3D codec equipped with this model consistently outperforms its 2D context model counterpart, for an extended test dataset. In this respect, we report a gain in lossless compression performance of up to 10%. Moreover, for a large range of bitrates, we always obtain gains in PSNR, sometimes even over 3dB.