李朋龙, 邓非, 李海亮, 李勇, 何江, 王岚. 基于有效区域约束的GPU-CPU协同影像快拼方法[J]. 武汉大学学报 ( 信息科学版), 2018, 43(2): 304-310. DOI: 10.13203/j.whugis20150284
引用本文: 李朋龙, 邓非, 李海亮, 李勇, 何江, 王岚. 基于有效区域约束的GPU-CPU协同影像快拼方法[J]. 武汉大学学报 ( 信息科学版), 2018, 43(2): 304-310. DOI: 10.13203/j.whugis20150284
LI Penglong, DENG Fei, LI Hailiang, LI Yong, HE Jiang, WANG Lan. A Method of GPU-CPU Co-processing Rapid Images Mosaicking Based on Valid Areas[J]. Geomatics and Information Science of Wuhan University, 2018, 43(2): 304-310. DOI: 10.13203/j.whugis20150284
Citation: LI Penglong, DENG Fei, LI Hailiang, LI Yong, HE Jiang, WANG Lan. A Method of GPU-CPU Co-processing Rapid Images Mosaicking Based on Valid Areas[J]. Geomatics and Information Science of Wuhan University, 2018, 43(2): 304-310. DOI: 10.13203/j.whugis20150284

基于有效区域约束的GPU-CPU协同影像快拼方法

A Method of GPU-CPU Co-processing Rapid Images Mosaicking Based on Valid Areas

  • 摘要: 提出了一种以有效区域约束的Voronoi图为拼接线网络,利用GPU-CPU协同处理航空影像快速拼接方法。首先,基于成像有效区域生成有效区域约束的Voronoi图拼接线网络,解决了传统Voronoi图拼接线网络在低重叠度条件下拼接后影像局部区域不被覆盖的问题,然后利用GPU-CPU协同处理将正射纠正嵌入到影像拼接的过程中,并且只对每张影像的有效区域进行纠正,再通过选择配置优化和存储层次性优化进一步提高拼接效率。实验表明,对237张高分辨率航空影像进行快速正射纠正和拼接,本文算法较传统先纠正再拼接的方法效率提高近20倍,同时保证很高的拼接精度,可以满足应急测绘要求。

     

    Abstract: A method for rapid mosaicking aerial images is introduced, based on GPU-CPU co-processing and a seamline network based on Voronoi diagrams, taking valid areas of the images into account. A seamline network is created based on a Voronoi diagram with the valid areas of the images, solving the problems occuring when some areas of a mosaiced image are not covered after mosaicking. This approach is based on the traditional Voronoi diagram network under low overlap conditions. Orthorectification is embedded in the mosaicking process during GPU-CPU co-processing, and only the valid area of each image is orthorectified. Meanwhile, the mosaicking efficiency is further improved by optimizing the configuration and the hierarchical memory of the GPU. Experimental results indicate that efficiency was increased by 20 times when mosaicking 237 high-resolution aerial images, and much faster than traditional methods which complete orthorectification of the aerial images before mosaicking. The precision of the mosaicked DOM was very high, thus meeting emergency mapping requirements.

     

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