6533b838fe1ef96bd12a3a78
RESEARCH PRODUCT
Space-Frequency Quantization using Directionlets
Vladan VelisavljevicMartin VetterliBaltasar Beferull-lozanosubject
Computational complexity theorybusiness.industryWavelet transformBasis functionIterative reconstructionSet partitioning in hierarchical treesComputer visionArtificial intelligencebusinessQuantization (image processing)AlgorithmData compressionImage compressionMathematicsdescription
In our previous work we proposed a construction of critically sampled perfect reconstruction transforms with directional vanishing moments (DVMs) imposed in the corresponding basis functions along different directions, called directionlets. Here, we combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT). We show that our new compression method outperforms the standard SFQ as well as the state-of-the-art compression methods, like SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the standard SFQ algorithm.
year | journal | country | edition | language |
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2007-01-01 | 2007 IEEE International Conference on Image Processing |