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Remote Sens. 2018, 10(1), 96; doi:10.3390/rs10010096

Adaptive Window-Based Constrained Energy Minimization for Detection of Newly Grown Tree Leaves

1
Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Douliu 64002, Taiwan
2
Department of Forestry and Natural Resources, National Chiayi University, Chiayi 60004, Taiwan
*
Author to whom correspondence should be addressed.
Received: 23 November 2017 / Revised: 23 December 2017 / Accepted: 8 January 2018 / Published: 12 January 2018
(This article belongs to the Special Issue Hyperspectral Imaging and Applications)

Abstract

Leaf maturation from initiation to senescence is a phenological event of plants that results from the influences of temperature and water availability on physiological activities during a life cycle. Detection of newly grown leaves (NGL) is therefore useful for the diagnosis of tree growth, tree stress, and even climatic change. This paper applies Constrained Energy Minimization (CEM), which is a hyperspectral target detection technique to spot grown leaves in a UAV multispectral image. According to the proportion of NGL in different regions, this paper proposes three innovative CEM based detectors: Subset CEM, Sliding Window-based CEM (SW CEM), and Adaptive Sliding Window-based CEM (AWS CEM). AWS CEM can especially adjust the window size according to the proportion of NGL around the current pixel. The results show that AWS CEM improves the accuracy of NGL detection and also reduces the false alarm rate. In addition, the results of the supervised target detection depend on the appropriate signature. In this case, we propose the Optimal Signature Generation Process (OSGP) to extract the optimal signature. The experimental results illustrate that OSGP can effectively improve the stability and the detection rate. View Full-Text
Keywords: hyperspectral detection; target detection; sprout detection; constrained energy minimization; iterative algorithm; adaptive window hyperspectral detection; target detection; sprout detection; constrained energy minimization; iterative algorithm; adaptive window
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, S.-Y.; Lin, C.; Tai, C.-H.; Chuang, S.-J. Adaptive Window-Based Constrained Energy Minimization for Detection of Newly Grown Tree Leaves. Remote Sens. 2018, 10, 96.

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