Abstract
In many applications, the amount and resolution of digital images have significantly increased over the past few years. For this reason, there is a growing interest for techniques allowing to efficiently browse and seek information inside such huge data spaces. JPEG 2000, the latest compression standard from the JPEG committee, has several interesting features to handle very large images. In this paper, these features are used in a coarse-to-fine approach to retrieve specific information in a JPEG 2000 code-stream while minimizing the computational load required by such processing. Practically, a cascade of classifiers exploits the bit-depth and resolution scalability features intrinsically present in JPEG 2000 to progressively refine the classification process. Comparison with existing techniques is made in a texture-retrieval task and shows the efficiency of such approach.
This work has been supported by the SIMILAR Network of Excellence.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Boliek, M., Christopoulos, C., Majani, E.: JPEG 2000 image core coding system (Part 1). Technical report, ISO/IEC JTC1/SC29 WG1 (2001)
Fleuret, F., Geman, D.: Coarse-to-fine face detection. International Journal of Computer Vision 41, 85 (2001)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: IEEE Conference on CVPR, pp. 609–615 (2001)
Mandal, M.K., Liu, C.: Efficient image indexing techniques in the JPEG 2000 domain. Journal of Electronic Imaging 13, 179–187 (2004)
Tabesh, A., Bilgin, A., Krishnan, K., Marcellin, M.W.: JPEG 2000 and motion jpeg 2000 content analysis using codestream length information. In: Proceedings of the Data Compression Conference (DCC 2005) (2005)
Neelamani, R., Berkner, K.: Adaptive representation of JPEG 2000 images using header-based processing. In: IEEE International Conference on Image Processing (ICIP), vol. 1, pp. I–381– I–384 (2002)
Xiong, Z., Huang, T.S.: Subband-based, memory-efficient JPEG 2000 images indexing in compressed-domain. In: SSIAI (ed.), pp. 290–294 (2002)
Jiang, J., Guo, B., Li, P.: Extracting shape features in JPEG 2000 compressed images. In: Yakhno, T. (ed.) ADVIS 2002. LNCS, vol. 2457, pp. 123–132. Springer, Heidelberg (2002)
MIT Vision and Modeling group: Vision texture (vistex) database (2002)
Do, M.N., Vetterli, M.: Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance. IEEE Trans. Image Process 11 (2002)
Mallat, S.: A Wavelet Tour of Signal Processing, p. 577. Academic Press, London (1998)
Descampe, A., DeVleeschouwer, C., Iregui, M., Macq, B., Marques, F.: Pre-fetching strategies for remote and interactive browsing of JPEG 2000 images. In: International Conference on Image Processing, ICIP 2006 ( to appear, 2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Descampe, A., Vandergheynst, P., De Vleeschouwer, C., Macq, B. (2006). Coarse-to-Fine Textures Retrieval in the JPEG 2000 Compressed Domain for Fast Browsing of Large Image Databases. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_38
Download citation
DOI: https://doi.org/10.1007/11848035_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39392-4
Online ISBN: 978-3-540-39393-1
eBook Packages: Computer ScienceComputer Science (R0)