Abstract
In this paper, we propose an efficient image retrieval method that extracts features through partial entropy decoding from JPEG-2000 compressed images. Main idea of the proposed method is to exploit the context information that is generated during context-based arithmetic encoding/decoding with three bit-plane coding passes. In the framework of JPEG-2000, the context of a current coefficient is determined depending on pattern of the significance and/or sign of its neighbors. One of nineteen contexts is at least assigned to each bit of wavelet coefficients starting from MSB (most significant bit) to LSB (least significant bit). As the context contains the directional variation of the corresponding coefficient’s neighbors, it represents the local property of image. In the proposed method, the similarity of given two images is measured by the difference between their context histograms in bit-planes. Through simulations, we demonstrate that our method achieves good performance in terms of the retrieval accuracy as well as the computational complexity.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Information technology, JPEG-2000 image coding system, ISO/IEC International Standard 15444-1, ITU Recommendation T.800 (2000)
Rabbani, M., Joshi, R.: An overview of the JPEG 2000 still image compression standard. Signal Processing: Image Communication 17(1), 3–48 (2000)
Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. 22(12), 1349–1380 (2000)
Smith, J.R., Chang, S.F.: Automated binary texture feature sets for image retrieval. In: Proc. ICASSP, Atlanta, May 1996, vol. 4, pp. 2239–2242 (1996)
Mandal, M.K., Aboulnasr, T., Panchanathan, S.: Fast wavelet histogram techniques for image indexing. Computer Vision and Image Understanding 75(1-2), 99–110 (1999)
Lian, C.-J., Chen, K.-F., Chen, H.-H., Chen, L.-G.: Analysis and architecture design of block-coding engine for EBCOT in JPEG 2000. IEEE Trans. Circuit & System for Video Tech. 13(3), 219–230 (2003)
Feng, G., Jiang, J.: JPEG compressed image retrieval via statistical features. Pattern Recognition 36(4), 977–985 (2003)
Chang, C.-C., Chuang, J.-C., Hu, Y.-S.: Retrieving digital images from a JPEG compressed image database. Image and Vision Computing 22(6), 471–484 (2004)
Ni, L.: A novel image retrieval scheme in JPEG-2000 compressed domain based on tree distance. In: Qing, S., Gollmann, D., Zhou, J. (eds.) ICICS 2003. LNCS, vol. 2836, pp. 15–18. Springer, Heidelberg (2003)
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
Park, HJ., Jung, HY. (2006). JPEG-2000 Compressed Image Retrieval Using Partial Entropy Decoding. 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_55
Download citation
DOI: https://doi.org/10.1007/11848035_55
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)