数字高程模型数据小波压缩算法
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国家自然科学基金资助项目(10171109);国家高技术研究发展计划资助项目(2001AA35040);国家部委基金资助项目


The Research on Digital Elevation Mode Data CompressionArithmetic via Wavelets
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    摘要:

    针对海量DEM数据的存储和传输的问题,设计出一种高效的DEM数据的小波压缩算法。基于提升理论提出了一种包含自由变量t的紧支撑小波构造方法;通过选取合适的小波滤波器系数,基于提升的整数小波变换只需要整数加法、整数乘法和移位实现,运算速度快,便于硬件实现;选取参数t=1的整数9-7小波变换,其运算量接近整数5-3小波,但DEM数据压缩质量接近浮点的CDF9-7小波。实验证明该压缩算法对DEM数据有极佳的压缩效果,在保持地形形状和起伏特征的前提下,DEM数据可以压缩4096倍,PSNR>34DB。

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    To solve the problem of the store and transmission of vast DEM data, an efficient compression algorithm for DEM data is presented. A technique based on the lifting scheme is designed to construct the compactly supported wavelets whose coefficients are composed of free variables. By properly selecting the coefficients of the 9-7 wavelet filter and being associated with the lifting scheme, an efficient approach via wavelet for DEM data compression is developed. The integer wavelets based on the lifting scheme only used integral addition, integral multiplication and shift, so it can be fast and easily realized via the hardware. When t=1, the integral wavelet filters approximately have the same complexity as integer wavelets 5-3, but preserve approximate quality of the compressed DEM data with the well-known CDF9-7 wavelet filters. The experiments show that the method can compress DEM data very well. Provided that the terrain figure and hypsography are maintained, the DEM data's compression ratio is 4096 and PSNR>34DB.

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罗永,成礼智,陈波,等.数字高程模型数据小波压缩算法[J].国防科技大学学报,2005,27(2):118-123.
LUO Yong, CHENG LIZhi, CHEN Bo, et al. The Research on Digital Elevation Mode Data CompressionArithmetic via Wavelets[J]. Journal of National University of Defense Technology,2005,27(2):118-123.

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  • 收稿日期:2004-10-15
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  • 在线发布日期: 2013-03-25
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