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引文資料
題名:
應用透視投影轉換進行微型化多相機陣列之波段套合
書刊名:
航測及遙測學刊
作者:
詹鈞評
/
饒見有
/
黃倬英
/
劉暹
/
李文慶
作者(外文):
Jhan, Jyun-ping
/
Rau, Jiann-yeou
/
Huang, Cho-ying
/
Liu, Kircheis
/
Lee, William
出版日期:
2016
卷期:
21:3
頁次:
頁183-197
主題關鍵詞:
多相機陣列系統
;
多光譜影像
;
無人飛行載具
;
波段套合
;
MiniMCA
;
Multispectral image
;
UAV
;
Band registrati
原始連結:
連回原系統網址
相關次數:
被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
排除自我引用:0
共同引用:0
點閱:2
微型化多相機陣列 (Miniature Multiple Camera Array, MiniMCA)是由多個鏡頭組成的多光譜框幅式相機,能記錄可見光至近紅外光波譜資訊,且由於體積小重量輕,因此可藉由無人飛行載具 (Unmanned Aerial Vehicle, UAV)獲取高空間與時間解析度的多光譜遙測影像。 MiniMCA因每個鏡頭之透視中心與觀測方向皆不同,不僅各鏡頭具有不同的透鏡畸變量,且相機之間亦存在著旋轉與平移的幾何轉換關係,使得原始多光譜影像具有很大的波段錯位現象。因此本研究提出 MiniMCA相機的波段套合程序,首先藉由室內相機率定求得各相機之內方位與相對方位參數,進而得到透鏡畸變修正與透視投影轉換參數,接著將所有副鏡頭之影像轉換至主鏡頭之像空間,最後結合系統性誤差修正 (含平移與透鏡畸變修正 )達到波段套合的目的。研究成果顯示經透視投影轉換與系統性誤差修正後相鄰波段間的平均套合誤差皆在0.2-0.5個像元之間,證明本研究提出之波段套合程序其精確度可符合遙感探測應用之需求。
以文找文
Miniature Multiple Camera Array (MiniMCA) is a frame-based multispectral sensor, which compose of multiple cameras with different filters to acquire images range from visible light to near infrared. Due to its light weight and small size, it is suitable for mounting on an Unmanned Aerial Vehicle (UAV) for acquiring high spatial, high temporal, and multispectral imagery. However, since all cameras have different perspective centers and view directions as well as different lens distortion effects, which will result in significant band-misregistration phenomena on the original images. In this study, a band registration scheme based on perspective transformation is thus proposed for MiniMCA sensor. It starts from indoor camera calibration to obtain the interior orientation parameters (IOPs) and relative orientation parameters (ROPs). Next, the slave images are transferred into the master camera’s image space through perspective transformation, where the coefficients are directly acquired from the estimated IOPs and ROPs. In the end, a systematic error correction (including displacement removal and lens distortion correction) is adopted to minimize the band misregistration effect. Through visual comparison and quantitative accuracy assessment, the experimental results show that the average of band misregistration errors are between 0.2 -0.5 pixels, which proves that the accuracy of the proposed scheme is accurate and satisfy the demand of remote sensing applications.
以文找文
期刊論文
1.
Rau, J. Y.、Yeh, P. C.(2012)。A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration。Sensors,12(8),11271-11293。
2.
Zitová, B.、Flusser, J.(2003)。Image registration methods: a survey。Image and vision computing,21(11),977-1000。
3.
Bay, H.、Ess, A.、Tuytelaars, T.、Van Gool, L.(2008)。Speeded-Up Robust Features (SURF)。Computer Vision and Image Understanding,110(3),346-359。
4.
Berni, J. A. J.、Zarco-Tejada, P. J.、Suarez, L.、Fereres, E.(2009)。Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle。IEEE Transactions on Geoscience and Remote Sensing,47(3),722-738。
5.
Calderón, R.、Navas-Cortés, J. A.、Lucena, C.、Zarco-Tejada, P. J.(2013)。High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices。Remote Sensing of Environment,139,231-245。
6.
Cho, W.、Schenk, T.(1992)。Resampling Digital Imagery to Epipolar Geometry。IAPRS International Archives of Photogrammetry and Remote Sensing,29(3),404-408。
7.
Debella-Gilo, M.、Kääb, A.(2011)。Sub-pixel precision image matching for measuring surface displacements on mass movements using normalized cross-correlation。Remote Sensing of Environment,115(1),130-142。
8.
Du, Q.、Raksuntorn, N.、Orduyilmaz, A.、Bruce, L. M.(2008)。Automatic Registration and Mosaicking for Airborne Multispectral Image Sequences。Photogrammetric Engineering & Remote Sensing,74(2),169-181。
9.
Kelcey, J.、Lucieer, A.(2012)。Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing。Remote Sensing,4(5),1462-1493。
10.
Laliberte, A. S.、Goforth, M. A.、Steele, C. M.、Rango, A.(2011)。Multispectral Remote Sensing from Unmanned Aircraft: Image Processing Workflows and Applications for Rangeland Environments。Remote Sensing,3(11),2529-2551。
11.
Rosten, E.、Porter, R.、Drummond, T.(2010)。Faster and better: a machine learning approach to corner detection。IEEE Transactions on Pattern Analysis and Machine Intelligence,32,105-119。
12.
Sankaran, S.、Maja, J. M.、Buchanon, S.、Ehsani, R.(2013)。Huanglongbing (citrus greening) detection using visible, near infrared and thermal imaging techniques。Sensors (Basel),13,2117-2130。
13.
Torres-Sanchez, J.、Lopez-Granados, F.、De Castro, A. I.、Pena-Barragan, J. M.(2013)。Configuration and specifications of an Unmanned Aerial Vehicle (UAV) for early site specific weed management。PloS one,8(3),e58210。
14.
Ye, Y.、Shan, J.(2014)。A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences。ISPRS Journal of Photogrammetry and Remote Sensing,90,83-95。
15.
Lowe, David G.(2004)。Distinctive Image Features from Scale-Invariant Keypoints。International Journal of Computer Vision,60(2),91-110。
會議論文
1.
Simper, A.(1996)。Correcting general band-to-band misregistrations。3rd IEEE International Conference on Image Processing,597-600。
圖書論文
1.
Dawn, S.、Saxena, V.、Sharma, B.(2010)。Remote Sensing Image Registration Techniques: A Survey。Image and Signal Processing。Springer。
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