a comparison of commercial pan-sharpening techniques for hr … · 2013-06-28 · 6/21/2013 rakesh...
TRANSCRIPT
A comparison of commercial Pan-sharpening techniques for HR Satellite imagery
Rakesh Kumar Mishra and Yun ZhangDepartment of Geodesy and Geomatics Engineering
University of New Brunswick
ESRI International User Conference 2013
6/21/2013 2 Rakesh K. Mishra
Contents
Why pansharpening ?
Pansharpening comparison
FuzeGo Pansharpening
Conclusion
6/21/2013 3 Rakesh K. Mishra
Importance of pan-sharpening
• More than 70% of optical satellites simultaneously collect a low resolution MS image and a high resolution Pan image.
• Most remote sensing and GIS applications desire high resolution colour image.
• Effective and high quality pan-sharpening technique is crucial for the success of many GIS/remote sensing applications.
• Research on pan-sharpening has been conducted since the mid-1980s.
6/21/2013 4 Rakesh K. Mishra
6/21/2013 5 Rakesh K. Mishra
Kodak’s patent
Yun Zhang’s paper
SpaceImaging’s patent
6/21/2013 6 Rakesh K. Mishra
Tens of thousands papers on pan-sharpening haves been published,
only a few outstanding pan-sharpening algorithms have been adopted by industry.
6/21/2013 7 Rakesh K. Mishra
Widely used commercial pan-sharpening algorithms
ERDAS IMAGINE:
• Subtractive Resolution Merge• HPF Resolution Merge • Modified IHS Resolution Merge• Wavelet Resolution Merge• Ehlers Fusion• HCS Resolution Merge• Resolution Merge
ENVI:
• CN Spectral Sharpening• Color Normalized(Brovey) • Gram-Schmidt• HSV Sharpening• PC Spectral Sharpening
6/21/2013 8 Rakesh K. Mishra
Widely used commercial pan-sharpening algorithms
ESRI:
• Brovey • ESRI • Gram-Schmid• IHS• Simple Mean
FuzeGo:
• UNB Pansharpening
HighView:
• Advanced Global Optimization
6/21/2013 9 Rakesh K. Mishra
Comparison among different pan-sharpening algorithmsData used for the pan-sharpening:
• IKONOS, 2002, Fredericton, Canada (Pan 540 MB, MS 135 MB)
• QuickBird, 2007, Beijing, China (Pan 820 MB, MS 205MB)
• GeoEye-1, 2009, Hobart, Australia (Pan 816 MB, MS 204 MB)
• WorldView-2, 2010, Moncton, Canada (Pan 131 MB, MS 65 MB).
All the images were in 16-bit format. All the MS bands were used in the test.
6/21/2013 10Rakesh K. Mishra
Pan-sharpening evaluation
Visual Analysis
Quantitative Analysis
There is no consensus on quantitative evaluation methods
6/21/2013 11Rakesh K. Mishra
All the images are displayed under the same visualization condition, i.e.
• The same area of the images before and after pan-sharpening are displayed, and
• The same histogram stretching is applied to all the images.
Comparison Results
6/21/2013 12Rakesh K. Mishra
Can not process images with more then 4 bands.
23/07/2012 12
6/21/2013 13Rakesh K. Mishra23/07/2012
6/21/2013 14Rakesh K. Mishra23/07/2012
6/21/2013 15Rakesh K. Mishra
Can not process images with more than 4 bands
23/07/2012 15
6/21/2013 16Rakesh K. Mishra23/07/2012 16
6/21/2013 17Rakesh K. Mishra23/07/2012 17
23/07/2012 18C. Pacwick, M. Deskevich, F. Pacifici, and S. Smallwood (2010): WorldView-2 PanSharpening. ASPRS 2010 Annual Conference, San Diego, California, April 26-30, 2010
(Kodak fusion)
WorldView-2 WorldView-2 (natural colour) (traditional)
(widely used) (newly developed in 2010)
(launched in 2009)
23/07/201219
00000000000000000000000111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111112222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000077777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////2222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222200000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
6/21/2013 20Rakesh K. Mishra
Comparison conclusions
• FuzeGo produces constant best results for all type of sensors and areas.
• Other techniques work well for some images or sensors, but not for others
• The second best technique is Gram-Schmidt (Kodak’s patent). But it produces poor results for WorldView-2 images.
• The third best technique is HCS, but still result is notconsistent.
6/21/2013 21Rakesh K. Mishra
Further examples of FuzeGO
IKONOS, July 2000San Diego, USA
FuzeGo
Original IKONOS Pan and MS images courtesy of Space Imaging Inc. (now GeoEye Inc.)
23/07/2012 22
23/07/2012 23
23/07/2012 24
23/07/2012 25
23/07/2012 26
23/07/2012 27
23/07/2012 28
23/07/2012 29
23/07/2012 30
23/07/2012 31
23/07/2012 32
23/07/2012 33
23/07/2012 34
23/07/2012 35
23/07/2012 36
23/07/2012 37
23/07/2012 38
23/07/2012 39
23/07/2012 40
QuickBird, May 2005Beijing, China
FuzeGo
Original QuickBird Pan and MS images courtesy of DigitalGlobe Inc.
23/07/2012 41
23/07/2012 42
23/07/2012 43
23/07/2012 44
23/07/2012 45
23/07/2012 46
23/07/2012 47
23/07/2012 48
23/07/2012 49
23/07/2012 50
23/07/2012 51
GeoEye-1, February 2009Hobart, Australia
FuzeGo
Original GeoEye-1 Pan and MS images courtesy of GeoEye Inc.
23/07/2012 52
23/07/2012 53
23/07/2012 54
23/07/2012 55
23/07/2012 56
23/07/2012 57
23/07/2012 58
GeoEye-1 satellite, original natural colour, 2mLaunched in 2008
23/07/2012 59
GeoEye-1, original B/W, 0.5m
23/07/2012 60
GeoEye-1, FuzeGo, 0.5m
23/07/2012 61
GeoEye-1, original natural colour, 2m8x enlarged
23/07/2012 62
GeoEye-1, original B/W, 0.5m2x enlarged
23/07/2012 63
GeoEye-1, FuzeGo, 0.5m2x enlarged
23/07/2012 64
WorldView-2, July 2010Moncton, Canada
FuzeGo
Original WorlView-2 Pan and MS images courtesy of DigitalGlobe Inc.
23/07/2012 65
www.DigitalGlobe.com
1 2 3 4 5 6 78
23/07/2012 66
23/07/2012 67
23/07/2012 68
23/07/2012 69
23/07/2012 70
23/07/2012 71
23/07/2012 72
23/07/2012 73
23/07/2012 74
23/07/2012 75
6/21/2013 76Rakesh K. Mishra
FuzeGo Software
http://www.fuzego.com/
6/21/2013 77Rakesh K. Mishra
FuzeGo in ENVI 5.1 Beta
FuzeGo achieves constant good fusion results regardless of the differences in sensors, areas and seasons.
Fully automatic
FuzeGo achieves:maximum detail increasing, minimum colour distortion, andoptimal colour and feature integration.
UNB-Pansharp has been widely recognized by industry
23/07/2012 78
Conclusion
23/07/2012 79
• DigitalGloble Inc. and GeoEye Inc. provided the original Pan and MS images.
• The comparative research was conducted at the University of New Brunswick, Canada.
• GEOIDE MDF program provided the funding for the research.
Acknowledgments
6/21/2013 80Rakesh K. Mishra