Region-of-interest coding based on set partitioning in hierarchical trees

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.