Automatic hotspot and sun glint detection in UAV multispectral images

Sensors (Switzerland)

Volumn 17, Issue 10, 2017, Pages

  Ortega Terol, Damian ^a   Hernandez Lopez, David ^b   Ballesteros, Rocio ^b   Gonzalez Aguilera, Diego ^a  

^a UNIVERSITY OF SALAMANCA   (Spain)

^b UNIVERSITY OF CASTILLA LA MANCHA   (Spain)

Author keywords

Flight planning and control; Hotspot; Image preprocessing; Photogrammetry; Remote sensing; Software development; Sun glint; UAV

Indexed keywords

AERIAL PHOTOGRAPHY; AIRCRAFT CONTROL; ERROR DETECTION; ERRORS; IMAGE ENHANCEMENT; IMAGE PROCESSING; PHOTOGRAMMETRY; PIXELS; PLANNING; RADIOMETRY; REMOTE SENSING; SOFTWARE DESIGN; SOFTWARE ENGINEERING; THREE DIMENSIONAL COMPUTER GRAPHICS; UNMANNED AERIAL VEHICLES (UAV);

DIGITAL TERRAIN MODEL; FLIGHT PLANNING; GROUND SAMPLE DISTANCES; HOT SPOT; IMAGE PREPROCESSING; PHOTOGRAMMETRY AND COMPUTER VISIONS; REMOTE SENSING APPLICATIONS; SUN GLINT;

AIRCRAFT DETECTION;

ARTICLE; PHOTOGRAMMETRY; REMOTE SENSING; SOFTWARE; SUN; VEGETATION;

EID: 85032031432     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s17102352     Document Type: Article

References (42)

1. Colomina, I.; Molina, P. Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS J. Photogramm. Remote Sens. 2014, 92, 79–97.
2. Gonzalez-Aguilera, D.; Rodriguez-Gonzalvez, P. Drones—An Open Access Journal. Drones 2017, 1, 1.
3. Hoffmann, H.; Nieto, H.; Jensen, R.; Guzinski, R.; Zarco-Tejada, P. J.; Friborg, T. Estimating evaporation with thermal UAV data and two-source energy balance models. Hydrol. Earth Syst. Sci. Discuss. 2016, 20, 697–713.
4. Díaz-Varela, R. A.; de la Rosa, R.; León, L.; Zarco-Tejada, P. J. High-Resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: Application in breeding trials. Remote Sens. 2015, 7, 4213–4232.
5. Valero, S.; Salembier, P.; Chanussot, J. Object recognition in hyperspectral images using binary partition tree representation. Pattern Recognit. Lett. 2015, 56, 45–51.
6. Balali, V.; Jahangiri, A.; Ghanipoor, S. Multi-class US traffic signs 3D recognition and localization via image-based point cloud model using color candidate extraction and texture-based recognition. Adv. Eng. Inform. 2017, 32, 263–274.
7. Yuqing, H.; Wenrui, D.; Hongguang, L. Haze removal for UAV reconnaissance images using layered scattering model. Chin. J. Aeronaut. 2016, 29, 502–511.
8. Ribeiro-Gomes, K.; Hernandez-Lopez, D.; Ballesteros, R.; Moreno, M. A. Approximate georeferencing and automatic blurred image detection to reduce the costs of UAV use in environmental and agricultural applications. Biosyst. Eng. 2016, 151, 308–327.
9. Bhardwaj, A.; Sam, L.; Akanksha; Javier Martín-Torres, F.; Kumar, R. UAVs as remote sensing platform in glaciology: Present applications and future prospects. Remote Sens. Environ. 2016, 175, 196–204.
10. Su, T. C. A study of a matching pixel by pixel (MPP) algorithm to establish an empirical model of water quality mapping, as based on unmanned aerial vehicle (UAV) images. Int. J. Appl. Earth Obs. Geoinf. 2017, 58, 213–224.
11. Teng, W. L.; Loew, E. R.; Ross, D. I.; Zsilinsky, V. G.; Lo, C.; Philipson, W. R.; Philpot, W. D.; Morain, S. A. Fundamentals of Photographic Interpretation, Manual of Photographic Interpretation, 2nd ed.; Philipson, W. R., Ed.; American Society for Photogrammetry and Remote Sensing: Bethesda, MD, USA, 1997; pp. 49–113.
12. Chen, J. M.; Cihlar, J. A hotspot function in a simple bidirectional reflectance model for satellite applications. Geophys. Res. 1997, 102, 907–925.
13. Pierrot-Deseilligny, M.; Clery, I. APERO, an open source bundle adjustment software for automatic calibration and orientation of set of images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2011, 38, 269–276.
14. Harmel, T.; Chami, M. Estimation of the sunglint radiance field from optical satellite imagery over open ocean: Multidirectional approach and polarization aspects. Geophys. Res. Oceans 2013, 118, 76–90.
15. Bréon, F. -M.; Maignan, F.; Leroy, M.; Grant, I. Analysis of hot spot directional signatures measured from space. Geophys. Res. 2002, 107, 4282.
16. Giles, P. Remote sensing and cast shadows in mountainous terrain. Photogramm. Eng. Remote Sens. 2001, 67, 833–840.
17. Dare, P. M. Shadow analysis in high-resolution satellite imagery of urban areas. Photogramm. Eng. Remote Sens. 2005, 71, 169–177.
18. Adeline, K. R. M.; Chen, M.; Briottet, X.; Pang, S. K.; Paparoditis, N. Shadow detection in very high spatial resolution aerial images: A comparative study. ISPRS J. Photogramm. Remote Sens. 2013, 80, 21–38.
19. Krahmer, F.; Lin, Y.; McAdoo, B.; Ott, K.; Wang, J.; Widemannk, D. Blind Image Deconvolution: Motion Blur Estimation; Technical Report; Institute of Mathematics and its Applications, University of Minnesota: Minneapolis, MN, USA, 2006.
20. Shan, Q.; Jia, J.; Agarwala, A. High-quality Motion Deblurring from a Single Image. ACM Trans. Gr. 2008, 27, 1–10.
21. Lelégard, L.; Brédif, M.; Vallet, B.; Boldo, D. Motion blur detection in aerial images shot with channel-dependent exposure time. In IAPRS; Part 3A; ISPRS Archives: Saint-Mandé, France, 2010; Volume XXXVIII, pp. 180–185.
22. Kay, S.; Hedley, J. D.; Lavender, S. Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: A Review of Methods for Visible and Near-Infrared Wavelengths. Remote Sens. 2009, 1, 697–730.
23. Goodman, J. A.; Lee, Z.; Ustin, S. L. Influence of Atmospheric and Sea-Surface Corrections on Retrieval of Bottom Depth and Reflectance Using a Semi-Analytical Model: A Case Study in Kaneohe Bay. Hawaii Appl. 2008, 47, 1–11.
24. Hochberg, E.; Andrefouet, S.; Tyler, M. Sea Surface Correction of High Spatial Resolution Ikonos Images to Improve Bottom Mapping in Near-Shore Environments. IEEE Trans. Geosci. Remote Sens. 2003, 41, 1724–1729.
25. Wang, M.; Bailey, S. Correction of Sun Glint Contamination on the SeaWiFS Ocean and Atmosphere Products. Appl. Opt. 2001, 40, 4790–4798.
26. Montagner, F.; Billat, V.; Belanger, S. MERIS ATBD 2. 13 Sun Glint Flag Algorithm; ACRI-ST: Biot, France, 2011.
27. Gordon, H.; Voss, K. MODIS Normalized Water-Leaving Radiance Algorithm Theoretical Basis Document (MOD 18); version 5; NASA:Washington, DC, USA, 2004.
28. Lyzenga, D.; Malinas, N.; Tanis, F. Multispectral Bathymetry Using a Simple Physically Based Algorithm. IEEE Trans. Geosci. Remote Sens. 2006, 44, 2251–2259.
29. Hedley, J.; Harborne, A.; Mumby, P. Simple and Robust Removal of Sun Glint for Mapping Shallow-Water Benthos. Int. J. Remote Sens. 2005, 26, 2107–2112.
30. Murtha, P. A.; Deering, D. W.; Olson, C. E., Jr.; Bracher, G. A. Vegetation. In Manual of Photographic Inter, 2nd ed.; Philipson, W. R., Ed.; Aamerican Society for Photogrammetry and Remote Sensing: Bethesda, MD, USA, 1997.
31. Sun, M. W.; Zhang, J. Q. Dodging research for digital aerial images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2008, 37, 349–353.
32. Camacho-de Coca, F.; Bréon, F. M.; Leroy, M.; Garcia-Haro, F. J. Airborne measurement of hot spot reflectance signatures. Remote Sens. Environ. 2004, 90, 63–75.
33. Huang, X.; Jiao, Z.; Dong, Y.; Zhang, H.; Li, X. Analysis of BRDF and albedo retrieved by kernel-driven models using field measurements. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2013, 6, 149–161.
34. Hernandez-Lopez, D.; Felipe-Garcia, B.; Gonzalez-Aguilera, D.; Arias-Perez, B. An Automatic Approach to UAV Flight Planning and Control for Photogrammetric Applications: A Test Case in the Asturias Region (Spain). Photogramm. Eng. Remote Sens. 2013, 1, 87–98.
35. González-Aguilera, D.; López-Fernández, L.; Rodriguez-Gonzalvez, P.; Guerrero, D.; Hernandez-Lopez, D.; Remondino, F.; Menna, F.; Nocerino, E.; Toschi, I.; Ballabeni, A.; et al. Development of an all-purpose free photogrammetric tool. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2016, XLI-B6, 31–38.
36. Tombari, F.; Di Stefano, L. Interest points via maximal self-dissimilarities. In Proceedings of the Asian Conference on Computer Vision, Singapore, Singapore, 1–5 November 2014; pp. 586–600.
37. Lowe, D. G. Object recognition from local scale-invariant features. In The Proceedings of the Seventh IEEE International Conference on Computer Vision; IEEE Computer Society: Washington, DC, USA, 1999; Volume 2, pp. 1150–1157.
38. Hartley, R.; Zisserman, A. Multiple View Geometry in Computer Vision; Cambridge University Press: New York, NY, USA, 2003; p. 655.
39. Kraus, K.; Jansa, J.; Kager, H. Advanced Methods and Applications Volume 2. Fundamentals and Standard Processes Volume 1; Institute for Photogrammetry Vienna University of Technology: Bonn, Germany, 1997.
40. Snavely, N.; Seitz, S. M.; Szeliski, R. Modeling the world from internet photo collections. Int. J. Comput. Vis. 2008, 80, 189–210.
41. Kukelova, Z.; Pajdla, T. A minimal solution to the autocalibration of radial distortion. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, USA, 17–22 June 2007; p. 7.
42. NDVI Camera—NGB Converted Canon S110 Camera. Available online:https://event38. com/product/ ndvi-camera-ngb-converted-canon-s110-camera/(accessed on 14 October 2017).