Bayesian object extraction from uncalibrated image pairs
Image Communication
Advances in Engineering Software
Foveated ROI compression with hierarchical trees for real-time video transmission
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
Medical ultrasound image compression using contextual vector quantization
Computers in Biology and Medicine
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In many image-coding applications such as Web browsing, image databases, and telemedicine, it is useful to reconstruct only a region of interest (ROI) before the rest of the image is reconstructed. In this paper, an ROI coding functionality is incorporated with the set partitioning in hierarchical trees (SPIHT) algorithm for wavelet-based image coding. By placing a higher emphasis on the transform coefficients pertaining to the ROI, the ROI is coded with higher fidelity than the rest of the image in earlier stages of progressive coding. The general thrust of this research is to identify necessary coefficients in the wavelet-transform domain for the decoder to reconstruct the desired region. This new method provides better performance than the previously presented methods