Joint singular value decomposition - a new tool for separable representation of images

IEEE International Conference on Image Processing

Volumn 2, Issue , 2001, Pages 569-572

  Pesquet Popescu, B ^a   Pesquet, J C ^a   Petropulu, A P ^a  

^a TELECOM PARISTECH   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; EIGENVALUES AND EIGENFUNCTIONS; IMAGE COMPRESSION; MATHEMATICAL TRANSFORMATIONS; OPTIMIZATION; STATISTICAL METHODS; VECTOR QUANTIZATION;

JOINT SINGULAR VALUE DECOMPOSITION; KARHUNEN-LOEVE TRANSFORM; TWO-DIMENSIONAL SEPARABLE APPROXIMATION;

IMAGE ANALYSIS;

EID: 0035167225     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Jacobi angles for simultaneous diagonalization
2. Combined techniques of singular value decomposition and vector quantization for image coding
3. Face recognition: Eigenfaces, elastic matching, and neural nets
4. An online image compression algorithm using singular value decomposition and adaptive vector quantization
5. Image coding using vector-embedded Karhunen-Loève transform
6. Signal processing based on multi-linear algebra