Precondition conjugate gradient block adjustment method based on sparse block matrix compression storage structure

• Main Authors: ZHENG MAOTENG, LUO XIANGANG, ZHOU SHUNPING, XU ZHANYA
• Format: Patent
• Language: Chinese; English
• Published: 20.07.2016
• Subjects: CALCULATING; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

The invention provides a precondition conjugate gradient block adjustment method based on a sparse block matrix compression storage structure. A large-scale sparse matrix compression storage algorithm is adopted, a large-scale method equation generated in big data block adjustment is subjected to compression storage and operation, the demand for memory is effectively reduced, a precondition conjugate gradient method iterative solution method equation is introduced aiming at an inversion problem of a compression matrix, direct inversion of the compression matrix is avoided, the storage and operation problem for the large-scale method equation in traditional block adjustment is solved, and the data processing capacity and efficiency are improved. The method is especially suitable for block adjustment of middle-large testing zone (500-10,000 images) data. 本发明提供了种基于稀疏块状矩阵压缩存储结构的预条件共轭梯度区域网平差方法，采用种大规模稀疏矩阵压缩存储算法，对大数据区域网平差中产生的大规模法方程进行压缩存储和运算，有效减少对内存的需求，同时针对压缩矩阵的求逆问题，引入预条件共轭梯度法迭代求解法方程，避免了对压缩矩阵的直接求逆，克服了传统区域网平差中对于大规模法方程