Article

An automated parallel image registration technique based on the correlation of wavelet features

Appl. Inf. Sci. Branch, NASA Goddard Space Flight Center, Greenbelt, MD
IEEE Transactions on Geoscience and Remote Sensing (impact factor: 2.89). 09/2002; DOI:10.1109/TGRS.2002.802501 pp.1849 - 1864
Source: IEEE Xplore

ABSTRACT With the increasing importance of multiple multiplatform remote sensing missions, fast and automatic integration of digital data from disparate sources has become critical to the success of these endeavors. Our work utilizes maxima of wavelet coefficients to form the basic features of a correlation-based automatic registration algorithm. Our wavelet-based registration algorithm is tested successfully with data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and the Landsat Thematic Mapper (TM), which differ by translation and/or rotation. By the choice of high-frequency wavelet features, this method is similar to an edge-based correlation method, but by exploiting the multiresolution nature of a wavelet decomposition, our method achieves higher computational speeds for comparable accuracies. This algorithm has been implemented on a single-instruction multiple-data (SIMD) massively parallel computer, the MasPar MP-2, as well as on the CrayT3D, the Cray T3E, and a Beowulf cluster of Pentium workstations.

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Keywords

Atmospheric Administration
 
comparable accuracies
 
correlation-based automatic registration algorithm
 
Cray T3E
 
critical
 
digital data
 
exploiting
 
high-frequency wavelet features
 
higher computational speeds
 
Landsat Thematic Mapper
 
MasPar MP-2
 
multiple multiplatform remote
 
National Oceanic
 
rotation
 
single-instruction multiple-data
 
TM
 
wavelet coefficients
 
wavelet decomposition
 
wavelet-based registration algorithm
 
work utilizes maxima
 

J. Le Moigne