Real-time middle wave infrared aerial image capturing and stitching system for vegetation observation

2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings Pub Date : 2015-05-11 DOI:10.1109/I2MTC.2015.7151408

Chun-Fu Lin, Sheng-Fuu Lin, Wen-Jyi Hwang, Yung-Hsinag Chen, C. Hwang

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引用次数: 3

Abstract

Over the last decades, several studies have demonstrated the reflectance effectiveness of middle wave infrared (MWIR) for discriminating among different types of vegetation, and estimating the total and leaf biomass of several forest ecosystems. Therefore, a MWIR aerial image capturing system for vegetation observation is urgently required. Furthermore, stitching those MWIR aerial images together is necessary for a panorama of the region of interest (ROI). Most traditional stitching algorithms for aerial images are designed for visible images, and are not suitable for infrared images that are noisy, blurry, or lack detail. In this paper, a novel real-time MWIR aerial image capturing and stitching system for vegetation observation is proposed. The proposed stitching algorithm for aerial infrared images improved from scale invariant feature transform (SIFT) and random M-least square can find a sufficient number of feature points easily and perform rapid calculations. Therefore, the proposed MWIR aerial image capturing and stitching system for vegetation observation can operate in real time.

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植被观测实时中波红外航拍拼接系统

在过去的几十年里，一些研究已经证明了中波红外(MWIR)在区分不同类型植被以及估计几种森林生态系统的总生物量和叶片生物量方面的有效性。因此，迫切需要一种用于植被观测的MWIR航拍系统。此外，将这些MWIR航空图像拼接在一起是必要的，以获得感兴趣区域(ROI)的全景。传统的航空图像拼接算法大多是针对可见光图像设计的，不适用于有噪声、模糊或缺乏细节的红外图像。提出了一种用于植被观测的MWIR实时航拍拼接系统。本文提出的航空红外图像拼接算法由尺度不变特征变换(SIFT)和随机m -最小二乘改进而成，可以方便地找到足够数量的特征点，计算速度快。因此，本文提出的MWIR植被观测航拍拼接系统可以实现实时运行。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings

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