The recent MPEG 4 and JPEG 2000 standards address the need for content based coding and manipulation of visual media. The upcoming MPEG 7 standard proposes content descriptors, which succinctly describe the visual content for the purpose of efficient retrieval. This implies that there is an impending need for efficient and effective joint compression and indexing approaches. Several compressed domain indexing techniques have been presented in the recent literature. These are based on the extraction of features from the compression parameters to derive the indices. However, there is little work in the domain of exploring the use of these features to serve the purposes of both compression and indexing. In this paper, we propose a novel technique for joint compression and indexing in the wavelet domain. We not that wavelet based compression is used in JPEG 2000 and (for texture coding) in MPEG 4. In the proposed technique, the wavelet decomposed image is first preprocessed to extract features which are then used for compressing the image as well as for deriving the indices. Extensive simulations have been performed in the JPEG 2000 compressed domain to demonstrate the efficiency of the proposed technique.
[1]
Mrinal Kumar. Mandal.
Wavelet-based coding and indexing of images and video.
,
1998
.
[2]
Shih-Fu Chang,et al.
An integrated approach for content-based video object segmentation and retrieval
,
1999,
IEEE Trans. Circuits Syst. Video Technol..
[3]
C.-C. Jay Kuo,et al.
WaveGuide: a joint wavelet-based image representation and description system
,
1999,
IEEE Trans. Image Process..
[4]
Sethuraman Panchanathan,et al.
Indexing spatial content of still texture in MPEG-4
,
2000,
2000 10th European Signal Processing Conference.
[5]
C.-C. Jay Kuo,et al.
Texture analysis and classification with tree-structured wavelet transform
,
1993,
IEEE Trans. Image Process..
[6]
B. S. Manjunath,et al.
A comparison of wavelet transform features for texture image annotation
,
1995,
Proceedings., International Conference on Image Processing.