Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28488
Title: Unified feature analysis in different compressed domains
Authors: Au, KM
Law, NF 
Siu, WC 
Keywords: Haar transforms
Data compression
Discrete cosine transforms
Feature extraction
Image coding
Low-pass filters
Wavelet transforms
Issue Date: 2003
Publisher: IEEE
Source: Proceedings of the 2003 Joint Conference of the Fourth International Conference on Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia, 15-18 December 2003, v. 1, p. 71-75 How to cite?
Abstract: Images can be compressed using different algorithms such as JPEG and JPEG 2000. Retrieving these kinds of images typically require processing them onto the uncompressed spatial form in which features are extracted for further analysis. This approach incurs many pre-processing operations, especially for large image archives. The objective of this paper is to study the features that are common in these domains so that indexing can be done directly from their compressed domain. By deriving expressions for the low pass filters in both block-based discrete cosine transform (DCT) and wavelet transform (WT), it is found that these two filters are very similar. In fact, it is shown that they are the same for the Haar wavelet kernel. Both theoretical and experimental studies have shown that the features common to DCT and WT domains can be extracted. Also, the effect of compression ratios on these two formulations have been studied. It is found that despite the high compression ratio, features that are extracted from these two compressed domains can still have a large similarity.
URI: http://hdl.handle.net/10397/28488
ISBN: 0-7803-8185-8
DOI: 10.1109/ICICS.2003.1292415
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