Stepwise-then-intelligent algorithm (STIA) for optimizing remotely sensed image rectification |
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| Authors: | Chang Li Jinxin Liu Xueyu Wang Xiaojuan Liu Yijin Wu |
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| Affiliation: | 1. Key Laboratory for Geographical Process Analysis and Simulation, Hubei Province, and College of Urban and Environmental Science, Central China Normal University, Wuhan, Chinalcshaka@126.com;3. Key Laboratory for Geographical Process Analysis and Simulation, Hubei Province, and College of Urban and Environmental Science, Central China Normal University, Wuhan, China |
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| Abstract: | ABSTRACTTo address the problems of parameter selection and accuracy optimization of models in image rectification, this article first proposes a novel stepwise-then-intelligent algorithm (STIA) for image rectification optimization, which includes the following steps. First, stepwise regression is suggested to simultaneously solve the over-parameterization problem and select the optimum parameters of the polynomial model and rational function model according to different terrains. Second, intelligent algorithms, e.g. the genetic algorithm (GA) and particle swarm optimization (PSO), are proposed to search for better results based on an innovative search range determined by the uncertainty propagation and 3-sigma rule. The experimental results show that the proposed STIA can achieve higher accuracy than conventional methods; and in most cases, the PSO algorithm used in STIA is superior to the GA used in STIA in measures of time and accuracy. Moreover, stepwise-then-PSO algorithm exhibits the best performance of all compared methods, including least squares, stepwise regression, total least squares and partial least squares. |
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