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.
Original language | English |
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Pages (from-to) | 605-610 |
Number of pages | 6 |
Journal | IEEE Transactions on Image Processing |
Volume | 7 |
Issue number | 4 |
DOIs | |
State | Published - 1998 |
Keywords
- Classification
- Discrete cosine transform
- Image coding
- Trellis-coded quantization
- Wavelet transform