基于提升小波的地形数据混合熵编码压缩与实时渲染

Terrain Data Hybrid Entropy Coding Compression Based on Lifting Wavelet and Real-time Rendering

高分辨率地形高程和影像数据给交互式3维地形可视化应用带来沉重压力,主要体现在数据存储、调度传输及实时渲染等方面。该文设计一种基于提升小波变换与并行混合熵编码的地形数据高性能压缩方法,并结合图形处理器(Graphics Process Unit,GPU)Ray-casting实现大规模3维地形可视化。首先建立多分辨率地形块的小波变换模型来映射其求精和化简操作;其次,基于提升小波变换分别构建格网数字高程模型(Digital Elevation Model,DEM)和地表纹理的多分辨率四叉树,对量化后的稀疏小波系数引入并行游程编码与并行变长霍夫曼编码相结合的混合熵编码进行压缩;将压缩数据组织成多序列层进码流进行实时解压渲染。在GPU上基于统一计算设备构架(Compute Unified Device Architecture,CUDA)实现该文的提升小波变换与混合熵编码。实验表明,在压缩比、信噪比与编解码的数据吞吐量综合指标方面,该文方法优于其它类似方法。实时渲染的高帧率满足了交互式可视化的要求。

High resolution terrain Digital Elevation Model （DEM） and orthophoto bring severely load including data storage, schedule and real-time rendering, etc.. A high performance terrain data compression method is proposed based on lifting wavelet transform and parallel hybrid entropy codec, and combined with Graphics Process Unit （GPU） Ray-casting to achieve large-scale 3D terrain visualization. First, the multi-resolution wavelet transform model of terrain tile is constructed to map the refinement and simplification operation. Then the multi-resolution quadtree of DEM and terrain texture is built separately based on lifting wavelet transform, the sparse wavelet coefficient generated from quantization is compressed by a hybrid entropy codec which combined with parallel run-length coding and variable-length Huffman coding. The compressed data are organized into progressive stream to do real-time decoding and rendering. The present lifting wavelet transform and hybrid entropy codec is implemented by Compute Unified Device Architecture （CUDA） in GPU. Experiment results show that the data compression ratio is effective with this method, PSNR and code-decode data throughput. High Frames Per Second （FPS） in real-time rendering satisfied the demand of interactive visualization.