Paper
15 January 1997 Indexing, retrieval, and browsing of wavelet compressed imagery data
Kai-Chieh Liang, Xia Wan, C.-C. Jay Kuo
Author Affiliations +
Abstract
The wavelet packet transform and the successive approximation quantization techniques, which have been adopted in modern wavelet coding, are exploited for content- based image retrieval in this research. By adopting this approach, images can be compressed and indexed simultaneously, and the complexity of database management can be significantly reduced. The proposed new feature for image indexing is the number of significant wavelet coefficients in each wavelet packet subband. This feature does not only serve as a good representation of image content but also allows a hierarchical retrieval and browsing of images and facilitates the progressive transmission of retrieved images. Extensive experimental results are provided to demonstrate the retrieval efficiency of the proposed new method.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kai-Chieh Liang, Xia Wan, and C.-C. Jay Kuo "Indexing, retrieval, and browsing of wavelet compressed imagery data", Proc. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); https://doi.org/10.1117/12.263441
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Wavelets

Image retrieval

Feature extraction

Databases

Image compression

Silicon

Quantization

Back to Top