Detection of leaf structures in close-range hyperspectral images using morphological fusion
Detection of leaf structures in close-range hyperspectral images using morphological fusion作者机构：Department of Telecommunications and Information Processing Ghent University-imec Ghent Belgium Facultad de Ingeniería en Eléctrica y Computación ESPOL Polytechnic University Escuela Superior Politécnica del Litoral Guayaquil Ecuador
出 版 物：《Geo-Spatial Information Science》 (地球空间信息科学学报（英文）)
年 卷 期：2017年第20卷第4期
页 面：325-332页
核心收录：
学科分类：0303[法学-社会学] 0709[理学-地质学] 1002[医学-临床医学] 0708[理学-地球物理学] 0705[理学-地理学] 0813[工学-建筑学] 100214[医学-肿瘤学] 0833[工学-城乡规划学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学]
基 金：supported by the Flemish Interuniversity Council (VLIR) the FWO project[Data fusion for image analysis in remote sensing]
主 题：Hyperspectral fusion morphology plant biology
摘 要：Close-range hyperspectral images are a promising source of information in plant biology,in particular,for in vivo study of physiological *** this study,we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological *** detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation,disease infections,and environmental conditions have in *** tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote *** results demonstrate the efficiency of our fusion approach,with significant improvements over some conventional methods.
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