Adaptive image coding using spectral classification

被引:4
作者
Jafarkhani, H
Farvardin, N
机构
[1] Univ Maryland, Dept Elect Engn, College Pk, MD 20742 USA
[2] Univ Maryland, Syst Res Inst, College Pk, MD 20742 USA
基金
美国国家科学基金会;
关键词
classification; discrete cosine transform; image coding; trellis-coded quantization; wavelet transform;
D O I
10.1109/83.663509
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:605 / 610
页数:6
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