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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SUPER RESOLVED REMOTE SENSING BY FUSION OF MULTI SPECTRAL AND 
SPATIAL DATA 
E. Gur a , Z. Zalevsky b * and B. Javidi c 
a Faculty of Engineering, Shenkar College of Eng. & Design, Ramat Gan, 52526, Israel - gur.eran@gmail.com 
b School of Engineering, Bar Ilan University, Ramat Gan, 52900, Israel - zalevsz@eng.biu.ac.il 
c University of Connecticut Electrical & Computer Engineering Dept., USA - bahram@engr.uconn.edu 
KEY WORDS: Engineering, Processing, Retrieval, Algorithms, Image, Resolution, High resolution, Optical 
ABSTRACT: 
In this paper the authors present a super resolution approach which is based on iterative data fusion algorithms. The proposed data 
fusion can be implemented using a plurality of spectral images as well as a plurality of images with varied resolution generated from 
different regions of the field of view. The data fusion suggested in this paper is gradual, allowing the build up of one single high 
resolution image from low resolution images and partial high resolution images. The iterative procedure used in this paper is based 
on iterative ping-pong computation between the spatial domain and its spectral distribution, similar to the Gerchberg-Saxton 
approach but with dynamic parameters. The iterative approach enables the retrieval of high resolution data from mostly-low 
resolution data. In both approaches mentioned, one may mix high and low resolution information by the insertion of properly 
defined constrains, and achieve an enhanced image in terms of clarity, resolution, correlation with true data and contrast. 
Corresponding author.