Compression of digital elevation maps for fast and efficient search and retrieval

In this paper we consider the use of nonlinear max- and min-lifted integer wavelets encoded using set partitioning in hierarchical trees (SPIHT) for the compression and efficient data-retrieval of digital elevation maps (DEMs). Max- and min-lifted integer wavelets losslessly code data such that the regional maxima and minima are preserved at the coarsest scale, which facilitates efficient multiresolutional elevation searches. Of particular interest in this application are the effects of maxima/minima propagation between resolution scales, as well as the effects of the bit-plane layering of wavelet coefficients inherent in the SPIHT coder. This implementation of a DEM browsing system will be compared to one utilizing a standard 5/3 wavelet, such as is used in JPEG2000.