scholarly journals Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

Sensors ◽  
2015 ◽  
Vol 15 (5) ◽  
pp. 12053-12079 ◽  
Author(s):  
Wonseok Kang ◽  
Soohwan Yu ◽  
Seungyong Ko ◽  
Joonki Paik
Keyword(s):  
Super Resolution ◽  
Adaptive Regularization ◽  
Uav Images

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization

NeuroImage ◽  
2015 ◽  
Vol 118 ◽  
pp. 584-597 ◽  
Author(s):  
Sébastien Tourbier ◽  
Xavier Bresson ◽  
Patric Hagmann ◽  
Jean-Philippe Thiran ◽  
Reto Meuli ◽  
...  
Keyword(s):  
Total Variation ◽  
Brain Mri ◽  
Fetal Brain ◽  
Super Resolution ◽  
Adaptive Regularization

scholarly journals Super-resolution enhancement of UAV images based on fractional calculus and POCS

2018 ◽  
Vol 21 (1) ◽  
pp. 56-66 ◽  
Author(s):  
Junfeng Lei ◽  
Shangyue Zhang ◽  
Li Luo ◽  
Jinsheng Xiao ◽  
He Wang
Keyword(s):  
Fractional Calculus ◽  
Resolution Enhancement ◽  
Super Resolution ◽  
Uav Images

scholarly journals PRELIMINARY INVESTIGATION ON POSSIBILITY OF SUPER RESOLUTION OF UAV ORTHOIMAGES

2020 ◽  
Vol V-1-2020 ◽  
pp. 301-308
Author(s):  
R. Matsuoka ◽  
K. Fukue
Keyword(s):  
High Resolution ◽  
Image Acquisition ◽  
Preliminary Investigation ◽  
Super Resolution ◽  
3D Measurement ◽  
Low Resolution ◽  
Ordinary Method ◽  
Uav Images ◽  
Infrastructure Maintenance

Abstract. Since inspection of infrastructures using UAV images seems to be efficient, many systems for infrastructure maintenance using UAV images have been developed recently. For the purpose of more efficient image acquisition, we started an investigation on the possibility of super resolution (SR) of UAV images to obtain high-resolution (HR) orthoimages suitable for infrastructure maintenance. This paper reports an preliminary investigation using existing UAV images acquired for 3D measurement that were not be intended to be utilized for SR. We produced HR orthoimages by three SR methods: image interpolation of a single low-resolution (LR) image by cubic convolution, SR by resampling, and SR based on observation equations. Both SR by resampling and SR based on observation equations utilize multiple overlapping LR images. Results of the investigation demonstrate that SR based on observation equations using multiple overlapping images would be able to provide higher resolution orthoimages than those produced by an ordinary method. The results show that an inaccurate DSM utilized in SR processing degrades the quality of SR results as well. Furthermore, the results illustrate that the quality of the result of SR processing depends rather upon the characteristic of a lens utilized in image acquisition. We think that further investigations on SR using UAV images would be necessary in order to put SR to practical use.

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