In: Wagner W., Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
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1 st color pallet 2 nd color pallet 
Figure 3. Experimental results taken from airborne multi 
spectral sensor at mid infra-red of 3.8-4.1 micron (left image of 
upper row) and at wavelength of and 4.5-4.8 micron (right 
image of upper row). In the lower row one may see the 
reconstructed result (left) and the obtained cross section (right). 
An improvement of more than 10% in the contrast is obtained 
when comparing the reconstruction (red) and the original image 
at low resolution (longer wavelength). 
CONCLUSIONS 
Gur E. and Zalevsky Z., 2007a. Single image digital super 
resolution: A revised Gerchberg-Papoulis algorithm. IAENG 
Int. Journal of Computer Science 34, pp. 251-255. 
Gur E. and Zalevsky Z., 2007b. Iterative single-image digital 
super-resolution using partial high-resolution data. Lecture 
Notes in Engineering and Computer Science, WCE2007, pp 
630-634. 
Joshi M., Chaudhuri S. and Panuganti R., 2005. A learning- 
based method for image super-resolution from zoomed 
observations. IEEE Transactions on Systems, Man, and 
Cybernetics, Part B 35, pp. 527-537. 
Misell D. L., 1973a. An examination of an iterative method for 
the solution of the phase problem in optics and electron optics: 
I. Test calculations. J. Phys. D: Appl. Phys. 6, pp. 2200-2216. 
Misell D. L., 1973b. A method for the solution of the phase 
problem in electron microscopy. J. Phys. D: Appl. Phys. 6, L6- 
L9. 
Misell D. L., 1973c. An examination of an iterative method for 
the solution of the phase problem in optics and electron optics: 
II. Sources of error. J. Phys. D: Appl. Phys. 6, pp. 2217-2225. 
Nguyen N. and Milanfar P., 2000. A wavelet-based 
interpolation-restoration method for super resolution. Journal of 
Circuit Systems Signal Process 19, Springer, pp. 321-338. 
Papoulis A., 1975. A new algorithm in spectral analysis and 
band-limited extrapolation. IEEE Trans. Circuits Syst. 22, pp. 
735-742. 
In this paper, the authors have presented a generalized approach 
for digital super resolution while using a plurality of images 
with different resolutions corresponding to either different 
regions of the field of view of the scene or from a multi spectral 
imager. The proposed algorithm was experimentally tested on 
images downloaded from an airborne camera capturing an 
urban scene at different resolutions and different wavelengths. 
Resolution improvement by a factor of two was observed in the 
reconstructed image by comparing it with an experimentally 
captured reference image. In addition, a contrast improvement 
of more than 10% was observed. 
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