Embedded zerotree wavelets coding based on adaptive fuzzy clustering for image compression
Image and Vision Computing
A video coding scheme based on joint spatiotemporal and adaptive prediction
IEEE Transactions on Image Processing
Multiresolution histogram analysis for color reduction
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Exploiting visual word co-occurrence for image retrieval
Proceedings of the 20th ACM international conference on Multimedia
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This paper presents a complete general-purpose method for still-image compression called adaptive prediction trees. Efficient lossy and lossless compression of photographs, graphics, textual, and mixed images is achieved by ordering the data in a multicomponent binary pyramid, applying an empirically optimized nonlinear predictor, exploiting structural redundancies between color components, then coding with hex-trees and adaptive runlength/Huffman coders. Color palettization and order statistics prefiltering are applied adaptively as appropriate. Over a diverse image test set, the method outperforms standard lossless and lossy alternatives. The competing lossy alternatives use block transforms and wavelets in well-studied configurations. A major result of this paper is that predictive coding is a viable and sometimes preferable alternative to these methods