Detection of leaf structures in close-range hyperspectral images using morphological fusion
Villegas, Gladys and Liao, Wenzhi and Criollo, Ronald and Philips, Wilfried and Ochoa, Daniel and Huang, Xin and Li, Jiayi and Chanussot, Jocelyn (2017) Detection of leaf structures in close-range hyperspectral images using morphological fusion. Geo-spatial Information Science, 20 (4). pp. 325-332. ISSN 1009-5020 (https://doi.org/10.1080/10095020.2017.1399673)
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Abstract
Close-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The 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 plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods.
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Item type: Article ID code: 69400 Dates: DateEvent29 November 2017Published24 May 2017AcceptedSubjects: Science > Physics Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 15 Aug 2019 13:48 Last modified: 11 Nov 2024 12:24 URI: https://strathprints.strath.ac.uk/id/eprint/69400