1. Image fusion
Goal: Combine higher spatial information in one band with higher spectral information in another dataset to create ‘synthetic’ higher resolution multispectral datasets and images

2. Motivation: why fuse ? Sharper image resolution (display)
Improved classification (and others)
More data types and bands available now
.. because we can

3. Sensors Panchromatic higher spatial resolution, visible wavelengths
some include NearIR since 1999
Why are they higher resolution ?
Multispectral:
Lower spatial resolution visible, NIR, … MIR, Thermal
May include MIR depending on date (more recent) and with a lower resolution (why ?)

4. SPOT technical band specs
SPOT 1-3 HRV m m Vis,NIR
SPOT m m MIR
SPOT /5m 10/20m
Pan band is in the visible spectrum (.5-.7) … ( )
Geobase orthoimage program
Coverage of Canada using a combination of SPOT 4 and 5 giving Pan and MS 10 /20m

5. ‘Medium-High’ resolution sensors: Landsat
Platform/Sensor date PAN MS (m) Thermal
Landsat TM 4/ /
Landsat ETM (-03)
Pan is Visible + NIR ( microns)
[Landsat MSS – 80m Vis/NIR ]

6. Cranbrook Hill, SPOT image 10m PAN and 20m MS

7. FUSE and IMGFUSE

8. IMGFUSE 432 and 234
432 RGB RGB

9. Cranbrook Hill – famous spots
1. Dreamcatcher movie 2003 (cabin) Cranbrook Hill airport ? Maps/GIS

10. SPOT PAN

11. Pan – Landsat 7

12. SPOT 20m MS

13. FUSE

14. NIR/Red ratio – SPOT 20m MS data

15. NIR / Red SPOT fused 10m data

17. RGB and IHS colour models
IHS Interactive colour wheel:
RGB model

18. Fusing Method
“IHS transformation”
RGB image -> HSI
Hue,Saturation, Intensity
The intensity channel is replaced by the high res (PAN) channel and the transformation is reversed: HIS -> RGB

19. Problems with fuse / IHS
Colour shift
Spectral fidelity
Partly solved by ??
HIS v FUSE
PANSHARP v FUSE
IMGFUSE v FUSE

20. NWT Geomatics imagery http://www. gnwtgeomatics. nt

21. Wunderle et al, IJRS 2007: Regenerating forest structure estimation using SPOT-5 pan-sharpened imagery
10m MS bands b. 2.5m fused image
Examined texture, and NDMI= SPOT `(3-4)/(3+4) versus forest structure
Needed high resolution AND mid-IR ; used PCI PANSHARP

22. Combine from same or different sensors
MODIS (Vis/NIR) MIR 1km TIR
SPOT – Landsat
Landsat – MODIS
MODIS – RADARSAT
Orthophotos – Satellite Imagery
Max 5: 1 maximum ratio recommended (?)

23. FUSION OF MODIS AND RADARSAT DATA FOR CROP TYPE CLASSIFICATION G
FUSION OF MODIS AND RADARSAT DATA FOR CROP TYPE CLASSIFICATION G. Hong , Y. Zhang , A. Zhangb, F. Zhou b J. Li MODIS: 250 / 500 m res. Radarsat: 12.5 m -> 25m

24. Fusion Technique to Extract Detail Information from Moderate Resolution Data for Global Scale Image Map Production Francis X.J. Canisius, Hugh Turral

25. The Principal Components Analysis method
Run PCA on the Multispectral data
Create PC1, PC2, PC3
Replace PC1 (brightness) with the higher res PAN band
Retransform PCA (decorrelate) back to RGB

27. Very high resolution sensors
Sensor date Pan MS (res: m)
Ikonos
Quickbird
Orbview RIP 2003
ALOS
Worldview
Worldview
Formosat
GeoEye
SPOT /
Cartosat (no MS)
EROS A, B 2000/ / (no MS)
Rapideye x

28. (very) High resolution imagery = < 10 metres
Ikonos
Quickbird
GeoEye
Worldview I
Worldview II
Cartosat 1 (India)
EROS A, B (Israel)
ALOS-PRISM
SPOT 5 (France)
Monitor-E (Russia)
Korona – keyhole
RapidEye 1-5 (Germany)
TerraSAR (Germany)
Task: research and describe one of these in a 4 slide powerpoint