Finding sparse representation of quantized frame coefficients using 0-1 integer programming

The use of overcomplete dictionaries, or frames, has received increased attention in low-bit-rate compression. Several vector selection algorithms, such as Matching Pursuit, Orthogonal Matching Pursuit and FOCUSS have been developed to get sparse representations of signals. In these algorithms, cont...

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Veröffentlicht in:	ISPA 2001 : proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis : in conjunction with 23nd [sic] Int'l Conference on Information Technology Interfaces : Pula, Croatia, June 19-21, 2001 S. 541 - 544
Hauptverfasser:	Ryen, T., Aase, S.O., Husoy, J.H.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	Piscataway NJ IEEE 2001 IEEE Service Center
Schlagworte:	Applied sciences Bit rate Dictionaries Distortion measurement Exact sciences and technology Information, signal and communications theory Linear programming Matching pursuit algorithms Pursuit algorithms Quantization Signal analysis Signal and communications theory Signal representation. Spectral analysis Signal, noise Sparse matrices Telecommunications and information theory Vectors Integer programming Signal compression Optimal solution Signal processing Low bit rate Signal representation Algorithm
ISBN:	9539676940, 9789539676948
Online-Zugang:	Volltext
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