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