Entropy-constrained SBPVQ for image coding

Author

Cohen, Robert ; Woods, John

Author_Institution

Dept. of Electr., Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA

fYear

1990

fDate

3-6 Apr 1990

Firstpage

2269

Abstract

An entropy-constrained algorithm for a type of finite-state vector quantizer called sliding-block predictive vector quantization (SBPVQ) is presented. This coding algorithm searches small codebooks to achieve high performance at low coding rates. Results from training the coder on a set of monochrome images and then testing it on an image outside the training set are presented. Also, three parallel entropy-constrained SBPVQ coders are used to code 24-b/pixel color images. A total rate of less than 0.5 b/pixel is achieved with good performance by using this vector predictor variant

Keywords

data compression; encoding; picture processing; codebooks; color images; entropy-constrained algorithm; image coding; monochrome images; sliding-block predictive vector quantization; testing; training; Algorithm design and analysis; Color; Entropy; Feedback loop; Image coding; Pixel; Rate-distortion; Systems engineering and theory; Testing; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.116025

Filename

116025

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2932430