DocumentCode :
1742220
Title :
Perceptually and statistically decorrelated features for image representation: application to transform coding
Author :
Malo, Jesús ; Ferri, Francesc ; Navarro, Rafael ; Valerio, Roberto
Author_Institution :
Dpt. d´´Opt., Valencia Univ., Spain
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
238
Abstract :
Transform coding consists of a scalar quantization of the features of an image representation. These features should be independent enough to justify the scalar approach. The coefficients of the commonly used DCT representation still show some dependence that may reduce its efficiency. In this work, a perceptually inspired nonlinear transform is used to map the DCT into a new representation that largely reduces the statistical and perceptual relations between the coefficients thus improving the compression performance
Keywords :
decorrelation; image coding; image representation; statistical analysis; transform coding; DCT representation; compression performance; image representation; nonlinear transform; perceptual relations; perceptually decorrelated features; scalar quantization; statistical relations; statistically decorrelated features; transform coding; Covariance matrix; Decorrelation; Discrete cosine transforms; Humans; Image coding; Image processing; Image representation; Principal component analysis; Quantization; Transform coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.903529
Filename :
903529
Link To Document :
بازگشت