Adaptive image coding using spectral classification

Author

Jafarkhani, Hamid ; Farvardin, Nariman

Author_Institution

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

Volume

7

Issue

4

fYear

1998

fDate

4/1/1998 12:00:00 AM

Firstpage

605

Lastpage

610

Abstract

We present a new classification scheme, dubbed spectral classification, which uses the spectral characteristics of the image blocks to classify them into one of a finite number of classes. A vector quantizer with an appropriate distortion measure is designed to perform the classification operation. The application of the proposed spectral classification scheme is then demonstrated in the context of adaptive image coding. It is shown that the spectral classifier outperforms gain-based classifiers while requiring a lower computational complexity

Keywords

adaptive codes; adaptive signal processing; computational complexity; discrete cosine transforms; image classification; rate distortion theory; spectral analysis; transform coding; vector quantisation; wavelet transforms; adaptive DCT coding; adaptive discrete wavelet transform coding; adaptive image coding; computational complexity; distortion measure; gain-based classifiers; image blocks; spectral characteristics; spectral classification; vector quantizer; Bit rate; Computational complexity; Discrete cosine transforms; Discrete wavelet transforms; Distortion measurement; Image coding; Performance evaluation; Quantization; Signal design; Statistics;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.663509

Filename

663509