Remote sensing images matching of decomposed affine model via pixel migration

Author

Chen Tianze ; Li Yan ; Li Mengjun

Author_Institution

Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China

Volume

1

fYear

2012

fDate

21-25 Oct. 2012

Firstpage

681

Lastpage

686

Abstract

An approach of the edge feature matching of remote sensing images matching based on parameters decomposition of the affine transformation model is presented. Firstly, the adaptability of the affine transformation model used in the remote sensing images matching is analyzed, and parameters of the affine transformation model are decomposed. Secondly, the sum of squared gradient (SSG) similarity is constructed based on the edge feature in images, and the parameters of the special transformation model between the matching remote sensing images are solved with the Genetic Algorithms (GA) which is used to obtain the global optimum solution of the similarity. Finally, the performance of the approach is analyzed in theory and validated with remote sensing images matching experiments.

Keywords

affine transforms; edge detection; feature extraction; genetic algorithms; geophysical image processing; gradient methods; image matching; remote sensing; SSG similarity; affine transformation model; decomposed affine model; edge feature matching; genetic algorithm; global optimum solution; parameter decomposition; pixel migration; remote sensing image matching; sum of squared gradient; GA; affine transformation model; edge feature matching; parameters decomposition; pixel migration;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing (ICSP), 2012 IEEE 11th International Conference on

Conference_Location

Beijing

ISSN

2164-5221

Print_ISBN

978-1-4673-2196-9

Type

conf

DOI

10.1109/ICoSP.2012.6491579

Filename

6491579