TY - JOUR
T1 - Storage and retrieval of compressed images using wavelet vector quantization
AU - Idris, F.
AU - Panchanathan, S.
N1 - Funding Information:
The authors would like to acknowledge the ®nancial support of the Natural Sciences and Engineering Research Council of Canada ( NSERC).
PY - 1997/6
Y1 - 1997/6
N2 - Multimedia information systems require efficient storage of and access to the images in a database. Recently, several image indexing techniques have been reported in the literature. Although these techniques combine image compression and image indexing, additional computational and storage costs are required to compute and store the indices. In this paper, we propose a new technique based on wavelet vector quantization for the storage and retrieval of compressed images. Here, the images are first decomposed using wavelet transform followed by vector quantization of the transform coefficients. We note that similar images map to similar codewords. Hence, the labels corresponding to a wavelet-vector-quantized image constitute a feature vector which is used as an index to store and retrieve the image. In addition, the lowest-resolution subimage resulting from the wavelet decomposition serves as a visual icon for browsing purposes. We note that the index is generated at compression time and, hence, the proposed technique eliminates the need for a separate structure to store the indices. This increases the storage efficiency and provides fast access to the compressed images in the database.
AB - Multimedia information systems require efficient storage of and access to the images in a database. Recently, several image indexing techniques have been reported in the literature. Although these techniques combine image compression and image indexing, additional computational and storage costs are required to compute and store the indices. In this paper, we propose a new technique based on wavelet vector quantization for the storage and retrieval of compressed images. Here, the images are first decomposed using wavelet transform followed by vector quantization of the transform coefficients. We note that similar images map to similar codewords. Hence, the labels corresponding to a wavelet-vector-quantized image constitute a feature vector which is used as an index to store and retrieve the image. In addition, the lowest-resolution subimage resulting from the wavelet decomposition serves as a visual icon for browsing purposes. We note that the index is generated at compression time and, hence, the proposed technique eliminates the need for a separate structure to store the indices. This increases the storage efficiency and provides fast access to the compressed images in the database.
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U2 - 10.1006/jvlc.1997.0041
DO - 10.1006/jvlc.1997.0041
M3 - Article
AN - SCOPUS:0031164871
SN - 1045-926X
VL - 8
SP - 289
EP - 301
JO - Journal of Visual Languages and Computing
JF - Journal of Visual Languages and Computing
IS - 3
ER -