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• W2163771205 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." @default.
• W2163771205 created "2016-06-24" @default.
• W2163771205 creator A5012421273 @default.
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• W2163771205 date "2002-08-01" @default.
• W2163771205 modified "2023-10-16" @default.
• W2163771205 title "An automated parallel image registration technique based on the correlation of wavelet features" @default.
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• W2163771205 doi "https://doi.org/10.1109/tgrs.2002.802501" @default.
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