Setting priorities: a new SPIHT-compatible algorithm for image compression

Diego Dugatkin, Michelle Effros, Akram Aldroubi, Andrew F. Laine, Michael A. Unser
2000 Wavelet Applications in Signal and Image Processing VIII  
We introduce a new algorithm for progressive or multiresolution image compression. The algorithm improves on the Set Partitioning in Hierarchical Trees (SPIlT) algorithm by replacing the SPIlT encoder. The new encoder optimizes the multiresolution code performance relative to a user-defined probability distribution (or priority function) over the code's rates or resolutions. The new algorithm's decoder is identical to the SPIlT decoder. The resulting code achieves the optimal expected
more » ... e across resolutions subject to the constraints imposed by the use of the SPIHT decoder and the distribution (or priorities) over resolutions set by the user. The encoder optimization yields performance improvements at the rates or resolutions of greatest importance (according to the encoder's priority function) at the expense of performance degradation at low priority rates or resolutions. The algorithm is fully compatible at the decoder with the original SPIlT algorithm. In particular, the decoder requires no knowledge of the priority function employed at the encoder. Experimental results on an image containing both text and photographic material yield up to 0.86 dB performance improvement over SPIHT at the resolution of highest priority. allowed to proceed to a high enough rate. In order to guarantee eventual lossless performance, the algorithm describes each bit-plane to perfect accuracy. Unfortunately, the accurate description of some coefficients (e.g., isolated high energy coefficients in the highest frequency bands) is very expensive in rate and achieves little distortion benefit. While this expense may be justified if lossless coding (high-rate, 0-distortion) is the highest priority, it is often not
doi:10.1117/12.408670 fatcat:nznvvvnlqverne6ozkpdx6txee