Adaptive DCT image coding based on a three-component image model

Author

Ran, Xiaonong ; Farvardin, Nariman

Author_Institution

Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA

Volume

3

fYear

1992

fDate

23-26 Mar 1992

Firstpage

201

Abstract

The authors described a three-component image model developed based on psychovisual studies of the human visual system. This image model consists of the primary component which contains the strong edge information of the image, the smooth component which represents the background slow-intensity variations, and the texture component which contains the textures. Using the image model, an adaptive discrete cosine transform (DCT) image coder is developed in order to achieve high subjective performance at low bit rates (⩽0.5 b/pixel). The simulation results show that this adaptive DCT coder performs better than JPEG both objectively (in PSNR) and subjectively, especially at low bit rates

Keywords

discrete cosine transforms; image coding; image texture; DCT; adaptive discrete cosine transform; background slow-intensity variations; edge information; high subjective performance; image coding; low bit rates; primary component; psychovisual studies; smooth component; texture component; three-component image model; Bit rate; Discrete cosine transforms; Educational institutions; Humans; Image coding; Image reconstruction; Pixel; Psychology; Radio access networks; Visual system;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1520-6149

Print_ISBN

0-7803-0532-9

Type

conf

DOI

10.1109/ICASSP.1992.226216

Filename

226216