LOD(Level Of Detail,层次细节)技术是解决大规模地形实时渲染的关键技术之一,通过这种技术可以较好地简化场景的复杂度,减少图形显示的失真度,满足一定的实时性要求。传统的算法将四叉树和LOD技术相结合将大规模数字高程模型数据(DEM)...LOD(Level Of Detail,层次细节)技术是解决大规模地形实时渲染的关键技术之一,通过这种技术可以较好地简化场景的复杂度,减少图形显示的失真度,满足一定的实时性要求。传统的算法将四叉树和LOD技术相结合将大规模数字高程模型数据(DEM)进行分块,并对块内数据按照分辨率的大小分层存储。通过对四叉树的研究,在限制性四叉树的基础上引入预处理算法,提高了地形读取速度,增强了实时显示效果。该算法是基于限制性四叉树的一种高效的规则网格划分方法,内存开销少,降低了CPU的负担。实验结果表明该算法提高了地形导入的效率,能实现大规模地形的实时漫游。展开更多
Although the modified Goldstein filter based on the local signal-to-noise （SNR） has been proved to be superior to the classical Goldstein and Baran filters with more comprehensive filter parameter, its adaptation is...Although the modified Goldstein filter based on the local signal-to-noise （SNR） has been proved to be superior to the classical Goldstein and Baran filters with more comprehensive filter parameter, its adaptation is not always sufficient in the reduction of phase noise. In this work, the local SNR-based Goldstein filter is further developed with the improvements in the definition of the local SNR and the adaption of the filtering patch size. What＇s more, for preventing the loss of the phase signal caused by the excessive filtering, an iteration filtering operation is also introduced in this new algorithm. To evaluate the performance of the proposed algorithm, both a simulated digital elevation model （DEM） interferogram and real SAR deformation interferogram spanning the L＇ Aquila earthquake are carried out. The quantitative results from the simulated and real data reveal that up to 79.5% noises can be reduced by the new filter, indicating 9%-32% improvements over the previous local SNR-based Goldstein filter. This demonstrates that the new filter is not only equipped with sufficient adaption, but also can suppress the phase noise without the sacrifice of the phase signal.展开更多
文摘LOD(Level Of Detail,层次细节)技术是解决大规模地形实时渲染的关键技术之一,通过这种技术可以较好地简化场景的复杂度,减少图形显示的失真度,满足一定的实时性要求。传统的算法将四叉树和LOD技术相结合将大规模数字高程模型数据(DEM)进行分块,并对块内数据按照分辨率的大小分层存储。通过对四叉树的研究,在限制性四叉树的基础上引入预处理算法,提高了地形读取速度,增强了实时显示效果。该算法是基于限制性四叉树的一种高效的规则网格划分方法,内存开销少,降低了CPU的负担。实验结果表明该算法提高了地形导入的效率,能实现大规模地形的实时漫游。
基金Foundation item： Projects（40974006, 40774003） supported by the National Natural Science Foundation of China Project（NCET-08-0570） supported by the Program for New Century Excellent Talents in Universities of China+2 种基金 Proj ect（2011JQ001） supported by the Fundamental Research Funds for the Central Universities of China Project（PolyU 5155/07E） supported by the Research Grants Council （RGC） of the Hong Kong Special Administrative Region, China Project（CX2011B 102） supported by the Doctoral Research Innovation of Hunan Province, China
文摘Although the modified Goldstein filter based on the local signal-to-noise （SNR） has been proved to be superior to the classical Goldstein and Baran filters with more comprehensive filter parameter, its adaptation is not always sufficient in the reduction of phase noise. In this work, the local SNR-based Goldstein filter is further developed with the improvements in the definition of the local SNR and the adaption of the filtering patch size. What＇s more, for preventing the loss of the phase signal caused by the excessive filtering, an iteration filtering operation is also introduced in this new algorithm. To evaluate the performance of the proposed algorithm, both a simulated digital elevation model （DEM） interferogram and real SAR deformation interferogram spanning the L＇ Aquila earthquake are carried out. The quantitative results from the simulated and real data reveal that up to 79.5% noises can be reduced by the new filter, indicating 9%-32% improvements over the previous local SNR-based Goldstein filter. This demonstrates that the new filter is not only equipped with sufficient adaption, but also can suppress the phase noise without the sacrifice of the phase signal.
