Context quantization by kernel Fisher discriminant

Optimal context quantizers for minimum conditional entropy can be constructed by dynamic programming in the probability simplex space. The main difficulty, operationally, is the resulting complex quantizer mapping function in the context space, in which the conditional entropy coding is conducted. T...

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Veröffentlicht in:	IEEE transactions on image processing 2006-01, Vol.15 (1), p.169-177
Hauptverfasser:	Mantao Xu, Xiaolin Wu, Franti, P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Algorithms Applied sciences Artificial intelligence Computer science control theory systems Computer Simulation Context modeling Context quantization Counters Data Compression - methods Dynamic programming Entropy Entropy coding Exact sciences and technology Fisher discriminants Image coding image compression Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Information, signal and communications theory Kernel Kernels Mapping Mathematical analysis Models, Statistical Pattern recognition. Digital image processing. Computational geometry Pixel Probability Quantization Scalars Signal processing Signal Processing, Computer-Assisted Telecommunications and information theory Video compression
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