document: An automated parallel image registration technique based on the correlation of wavelet features 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 -LRB- NOAA -RRB- Advanced Very High Resolution Radiometer -LRB- AVHRR -RRB- and the Landsat Thematic Mapper -LRB- TM -RRB- , 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 -LRB- SIMD -RRB- 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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