基于小波变换和混合熵编码的山区格网DEM数据压缩

Mountain Grid DEM Data Compression Based on Wavelet Transform and Mixed Entropy Coding

用信息论的观点对山区格网DEM数据进行了分析 ,发现山区DEM数据具有信息熵高、冗余度低的特点 ,从而导致了无损压缩方法———熵编码对其进行压缩的压缩比低。为了实现对DEM数据高效、高精度的压缩 ,笔者提出利用具有线性相位的双正交小波变换以及混合熵编码方法 (Huffman编码加游程编码 )对山区格网DEM数据进行压缩。实验结果表明 ,该方法在基本不损失DEM数据精度的情况下 ,可获得比无损压缩方法高得多的压缩比。

In this paper,through analyzing the grid DEM data of mountain area in the view of informatics, it is discovered that the grid DEM data of mountain area has features of high information entropy and lower redundancy, which makes it impossible to gain high compression ratio(CR) by means of traditional lossless entropy coding method. In order to implement higher efficient compression,the authors put forward biorthogonal wavelet (with linear phase) transformation and mixed entropy coding method (Huffman coding and Run-length coding) for compressing the grid DEM data of mountain area. The experimental results prove that this method which the authors raise can not only ensure the precision of decompressed DEM data but also provide much more higher compression ratio of the DEM data.