Title :
Remote sensing image fusion techniques based on statistical model
Author :
Peng-bo Wang ; Yue-shan Liu ; Xian-zhong Wen ; Chun-sheng Li
Author_Institution :
Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
Abstract :
In this paper, a novel algorithm of remote sensing image fusion based on statistical model is presented. The main research goal of this study is to explore a new technique for remote sensing image fusion. By using the statistical features of SAR and optical images, fused image not only combines multi-source information, but also realizes speckle noise suppression. Local-window adaptive correction is achieved according to the relationship between the edge features and the current analysis point. Model parameters are estimated by the data of local-window. The proposed algorithm improves the performance of fusion processing, and helps preserve edge features. The fusion results between SAR image and optical image show the validity of the algorithm.
Keywords :
image fusion; interference suppression; optical images; radar imaging; remote sensing by radar; speckle; statistical analysis; SAR image; fused image; fusion processing; local-window adaptive correction; model parameter estimation; multisource information; optical images; remote sensing image fusion techniques; speckle noise suppression; statistical features; statistical model; Fusion Processing; Remote Sensing Image; Statistical Model;
Conference_Titel :
Information Science and Control Engineering 2012 (ICISCE 2012), IET International Conference on
Conference_Location :
Shenzhen
Electronic_ISBN :
978-1-84919-641-3
DOI :
10.1049/cp.2012.2435