Tehnički vjesnik, Vol. 25 No. 2, 2018.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20171023105844
Fusion of Multispectral and Panchromatic Images via Local Geometrical Similarity
Hong Li
orcid.org/0000-0002-6385-6354
; School of Computer Science, XianYang Normal University, XianYang, Shaanxi, 712000, China
Fenxia Wu
; School of Computer Science, XianYang Normal University, XianYang, Shaanxi, 712000, China
Xiaobo Zhang
; School of Computer Science, XianYang Normal University, XianYang, Shaanxi, 712000, China
Sažetak
A pansharpening method based on local geometrical similarity is proposed in this paper. According to the observation model, the relationships among low spatial resolution multispectral (LRMS), panchromatic (Pan) and high spatial resolution multispectral (HRMS) images are formulated. In this paper, in order to reduce the color distortion and enhance the spatial information of fused images, we propose a Pan-Sharpening method via Local Geometrical Similarity (PLGS). First, the structure similarity prior within a local region in the Pan image is employed to regularize the solution space to obtain a more accurate solution. Then, the prior is embedded into the LRMS image to enhance the spatial resolution. In order to capture better geometrical structure information, such as orientation information and geometric textures, the steerable kernel is used to calculate the similarity coefficients in a local window. Some experiments are considered on different datasets and the results show that the proposed method can improve the visual effect and the quantitative values.
Ključne riječi
local similarity; pansharpening; remote sensing images; steerable kernel
Hrčak ID:
199154
URI
Datum izdavanja:
21.4.2018.
Posjeta: 1.060 *