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結合光學與紅外線熱影像正射鑲嵌處理

Orthomosaic Processing based on Infrared Thermal and Optical Imagery

摘要


相較於傳統衛照與航照之遙感探測技術,無人機載具在機動性與量測精度上皆展現其優勢。本研究以建置稻作生命週期葉溫資料庫為目標,提出無人機光學與紅外線熱影像之自動化資料處理程序,協助後續針對稻作正常生長狀態、水分缺乏、養份缺乏、病蟲害等大量特徵分析作業,朝向精準農業經營與管理之目的。然而,目前紅外線熱影像的影像解析度仍遠不如光學影像,往往造成在影像內容判釋或特徵萃取處理上之難度。因此,本文著重於運用影像超解析重建技術提升紅外線熱影像之空間解析度,並同時提出可產製紅外線熱影像鑲嵌圖之架構,藉以提升農耕地熱數據的全面評估與判釋成效。實際稻作影像處理成果顯示,超解析重建技術相較於一般內插處理,除了可提升影像解析度亦可維持影像內容資訊,並驗證所提出方法進行正射熱影像鑲嵌圖製作之有效性。

並列摘要


Compared with traditional remote sensing and aerial photogrammetry technology, Unmanned aircraft vehicles (UAVs) show their advantages in mobility and measurement accuracy. In this study, we plan to establish a leaf temperature database for rice life cycle, and proposed an automated data processing scheme for UAV optical and infrared thermal imagery to assist in the follow-up analysis of rice growth, water deficiency, lack of nutrients, and pests and also to aim at precision agriculture management and management. However, at present, the resolution of infrared thermal images is still far inferior to optical images, which often results in difficulty in interpretation of image content or feature extraction processing. Therefore, this study focuses on the use of image super-resolution reconstruction technology to improve the spatial resolution of infrared thermal imaging and at the same time puts forward a scheme for producing infrared thermal image mosaic maps, so as to improve the comprehensive assessment and interpretation of thermal data of agricultural land.

延伸閱讀