To provide flexible and efficient geographic information services, a new asymptotic transmission method based on a linear binary line generalization (BLG) tree storage structure was proposed. First, we used a BLG tree to store all the hierarchical simplification results of the dynamic programming (DP) algorithm and modify the sub-node offsets. Then, we set different target scales and calculated the average distance between neighboring feature points to filter out the appropriate feature points. Finally, the protein inference algorithm (PIA) iteratively approximated the set using three non-uniform B-sample curves to improve the accuracy. The experiment results proved that the proposed could effectively improve the network transmission efficiency of vector map data.
KEYWORDS: Data modeling, Multiscale representation, Wavelets, Data storage, Wavelet transforms, Fourier transforms, Algorithms, Reconstruction algorithms, Mathematical modeling, Geographic information systems
This paper introduces the spline function approximation theory to the multiscale expression of map curves. For the complex shape of map curves, the large amount of data and multiscale characteristics, we first use the DP algorithm to obtain feature points under different thresholds, and integrating them with the minimum distance visible for the human eye, according to the different average distances between adjacent feature points, to select a suitable linear threshold change, the multiscale representation results when obvious differences are formed. The experiments show that, unlike traditional Fourier series and wavelet transform for the occurrence of point shifts at the feature points of the simplified curves, the PIA method can well balance the overall morphology of the simplified curves and the accuracy of local feature points, and it is feasible to establish a continuous multiscale representation model of map curves by using the method through the selection of continuous thresholds.
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