JPEG-2000 Compressed Image Retrieval Using Partial Entropy Decoding
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.
KeywordsImage Retrieval Query Image Context Modeling Retrieval Performance JPEG Compression
Unable to display preview. Download preview PDF.
- 1.Information technology, JPEG-2000 image coding system, ISO/IEC International Standard 15444-1, ITU Recommendation T.800 (2000)Google Scholar
- 3.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)Google Scholar
- 4.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)Google Scholar
- 9.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)Google Scholar