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Stepwise-then-intelligent algorithm (STIA) for optimizing remotely sensed image rectification

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成果类型:
期刊论文
作者:
Li, Chang*;Liu, Jinxin;Wang, Xueyu;Liu, Xiaojuan;Wu, Yijin
通讯作者:
Li, Chang
作者机构:
[Li, Chang] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei, Peoples R China.
[Li, Chang] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
通讯机构:
[Li, Chang] C
Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei, Peoples R China.
Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
语种:
英文
期刊:
International Journal of Remote Sensing
ISSN:
0143-1161
年:
2018
卷:
39
期:
21
页码:
7350-7369
基金类别:
National Natural Science Foundation of China (NSFC), ChinaNational Natural Science Foundation of China (NSFC) [41771493, 41101407]; Natural Science Foundation of Hubei Province, ChinaNatural Science Foundation of Hubei Province [2014CFB377, 2010CDZ005]; self-determined research funds of CCNU from the colleges' basic research and operation of MOE [CCNU15A02001]; Wuhan Youth Science and technology plan [2016070204010137]
机构署名:
本校为第一且通讯机构
院系归属:
城市与环境科学学院
摘要:
To 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 sear...

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