GeoEye Image Fusion Vegetation Information Extraction Based on Blue Noise Measurement Texture

7th International Conference on Environment and Industrial Innovation

生态环境科学;工业技术

Luo, Qiu^1 ; Xiong, Qiming^2 ; Liu, Yao^3 ; Zhang, Gui^2

School of Geosciences and Info-Physics, Central South University, China^1

Central South University of Forestry and Technology, China, China^2

Computational Geosciences Research Center, Central South University, China^3

关键词: Effective algorithms;    Fusion algorithms;    High resolution image segmentation;    Information acquisitions;    Parameter combination;    Spectral information;    Texture segmentation;    Vegetation information extraction;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/67/1/012007/pdf
DOI  :  10.1088/1755-1315/67/1/012007

来源: IOP

【 摘 要 】

Vegetation high-resolution image segmentation is an important kind of target, while how to fuse image by using spatial and spectral information of GeoEye image, and make effective determination of the scale of vegetation texture segmentation is an important topic. This paper presents an algorithm of GeoEye image fusion vegetation information extraction based on blue noise measurement texture, which the vegetation information spectral response is calculated based on fast Fourier transform, in order to obtain the texture gray scale distribution of vegetation information, thus realizing accurate extraction of vegetation information. The simulation result got by the algorithm shows the deviation between NDVI index and original value index is below 0.05, which is obviously better than those obtained with the two comparison fusion algorithms of PCA transform (smaller than 0.4) and Brovey (smaller than 0.25), and provides the best parameter combination form [120,0.34,0.48]. Hence, it is an effective algorithm for high accuracy GeoEye image vegetation information acquisition.