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ONLINE ADAPTIVE VECTOR QUANTIZATION WITH VARIABLE SIZE CODEBOOK ENTRIES
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AI
DOI：10.1016/0306-4573(94)90003-5.png)
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摘要
En 中文
We present a new image compression algorithm that employs some of the most successful approaches to adaptive lossless compression to perform adaptive online (single pass) vector quantization with variable size codebook entries. We have tested this algorithm with a host of standard test images (e.g., gray scale magazine images, medical images, space and scientific images, fingerprint images, and handwriting images) and with no prior knowledge of the data or training, for a given fidelity, the compression achieved typically equals or exceeds that of the JPEG standard. The only information that this algorithm needs in advance is the fidelity criterion. In addition, our algorithm is more flexible than standard VQ and provides tighter guarantees on fidelity.
Keyword:
COMPRESSION
SEQUENCES
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期刊
I
IF:
6.9
论文数:
5.2K
被引数:
1.4W
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