Automatic generalization of geographical information is the core content of multi-scale representation of spatial data, but
the scale dependent generalization methods are far from abundance because of its extreme complicacy. Most existing
algorithms about automatic generalization do not relate to scale directly or accurately, not forecast and control the
generalized effects, and cannot assess the global consistency of the generalized results. The rational and quantitative
methods and criterions of measuring the extent of generalization have not still been sought out.
Lifting Scheme is a new branch of Wavelet analysis burgeoning in last decades. It has several noteworthy aspects
comparing with the Binary wavelet Transformation. The fundamentals of Lifting Scheme and the three constructing steps,
which include Split step, Predict step and Merge step, are presented detailed in this paper. DEM can be represented in
multi-scale model by the methods of The Lifting Scheme and The Binary Wavelet Transform. Compare with two
methods, the Lifting Scheme has several superiorities by analyzing the experimental results: Firstly, the trend of relief
could be preserved in course of transforming; secondly, the Lifting Scheme can process the points of boundary of DEM
efficiently and the spatial data precision can also be maintained, and at last the calculation process of Lifting Scheme is
more speedy.
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