Fast wavelet histogram techniques for image indexing
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated binary texture feature sets for image retrieval
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04
Analysis and architecture design of block-coding engine for EBCOT in JPEG 2000
IEEE Transactions on Circuits and Systems for Video Technology
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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.