"Automatic Image Registration for Remote Sensing on Reconfigurable Computers"
Esam El-Araby1, Mohamed Taher1, Tarek El-Ghazawi1, and Jacqueline Le Moigne2
1The George Washington University
2NASA Goddard Space Flight Center
Many applications in remote sensing rely on image registration. These include three-dimensional mapping of the land and sea surface, identifying and mapping different types of land use, and aligning images. With the dramatic increase in data volumes and types of sensors, image registration became also crucial for content-based retrieval of remote sensing data and image data from large data repositories. Image registration is to determine the transformation between a newly sensed image and a reference image. In general, image registration is the process of superimposing two images and transforming one of them to find the best transform to make them match. The complexity of the search and similarity measurement in image registration could be computationally intensive. Computational time becomes even more critical with the current increase in data. This presents a challenge for traditional processing techniques. As a result, high performance image registration is needed.
The trend for remote sensing satellite missions has always been towards smaller size, lower cost, more flexibility, and higher computational power. Reconfigurable Computers (RCs) combine the flexibility of traditional microprocessors with the power of Field Programmable Gate Arrays (FPGAs). Therefore, RCs are a promising candidate for these types of problems.
This paper presents the design and implementation of an RC-based automatic image registration. We investigate the potential of using RCs for the domain of remote sensing by implementing the automatic image registration algorithm. Our results have been proven to provide high performance and high accuracy.
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