A Streaming Piecewise-Constant Model
DCC '99 Proceedings of the Conference on Data Compression
Context Quantization with Fisher Discriminant for Adaptive Embedded Wavelet Image Coding
DCC '99 Proceedings of the Conference on Data Compression
Content Layer Progressive Coding of Digital Maps
DCC '00 Proceedings of the Conference on Data Compression
Lossless compression of continuous-tone images via context selection, quantization, and modeling
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
Fast Motion Detection for Thin Client Compression
DCC '02 Proceedings of the Data Compression Conference
Mutual information-based context quantization
Image Communication
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Abstract: Context based entropy coding often faces the conflict of a desire for large templates and the problem of context dilution. We consider the problem of finding the quantizer Q that quantizes the K-dimensional causal context CI = (Xi - t1, Xi - t2,...,Xi - tK) of a source symbol Xi into one of M conditioning states. A solution giving the minimum adaptive code length for a given data set is presented (when the cost of the context quantizer is neglected). The resulting context quantizers can be used for sequential coding of the sequence X0 X1 X2, .... A coding scheme based on binary decomposition and context quantization for coding the binary decisions is presented and applied to digital maps and &alpha: -plane sequences. The optimal context quantization is also used to evaluate existing heuristic context quantizations.