System and method for encoding multidimensional data using hierarchical self-organizing cluster vector quantization
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United States of America Patent
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Apr 20, 2004
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N/A
app pub date -
Nov 24, 2000
filing date -
Nov 24, 2000
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Expired
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Abstract
The present invention relates to a method of encoding a hyper-spectral image datacube using vector quantization. According to the invention, a temporary codebook having a small number, n, of codevectors is generated from the datacube. The datacube is processed using the temporary codebook to form n clusters (subsets) of vectors. A codevector corresponds to a cluster and is the centre of gravity for the cluster. In the compression process, vectors in each cluster are encoded by the corresponding codevector. Then the reconstruction fidelity of the encoded cluster is evaluated. When the fidelity of an encoded cluster is better than a predetermined fidelity, the codevector relating to that cluster is stored in a final codebook and the vectors in the cluster are expressed with the index (address) of the codevector in the final codebook. When the fidelity of an encoded cluster is not suitable, the cluster is reencoded with a new temporary codebook generated from this cluster, and the same process is repeated. The compression process is recursively implemented until all clusters are processed.
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