Construction of a high-resolution digital map to support citrus breeding using an autonomous multicopter

[1]  David J. Kriegman,et al.  Robust structure and motion from outlines of smooth curved surfaces , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Soizik Laguette,et al.  Remote sensing applications for precision agriculture: A learning community approach , 2003 .

[3]  Michael Elad,et al.  Advances and challenges in super‐resolution , 2004, Int. J. Imaging Syst. Technol..

[4]  Yubin Lan,et al.  Development and prospect of unmanned aerial vehicle technologies for agricultural production management , 2013 .

[5]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[6]  Fabio Remondino,et al.  UAV PHOTOGRAMMETRY FOR MAPPING AND 3D MODELING - CURRENT STATUS AND FUTURE PERSPECTIVES - , 2012 .

[7]  Moon Gi Kang,et al.  Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..

[8]  M. Omid,et al.  Estimating volume and mass of citrus fruits by image processing technique , 2010 .

[9]  Kazuhito Sawase,et al.  An Efficient Super Resolution Based on Image Dimensionality Reduction Using Accumulative Intensity Gradient , 2014, J. Adv. Comput. Intell. Intell. Informatics.

[10]  Jose A. Jiménez-Berni,et al.  Pheno-Copter: A Low-Altitude, Autonomous Remote-Sensing Robotic Helicopter for High-Throughput Field-Based Phenotyping , 2014 .

[11]  Chunhua Zhang,et al.  The application of small unmanned aerial systems for precision agriculture: a review , 2012, Precision Agriculture.

[12]  Pablo J. Zarco-Tejada,et al.  Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle , 2009, IEEE Transactions on Geoscience and Remote Sensing.