Abstract
This paper presents an efficient real time implementation of the regularized matched spatial filter algorithm (R-MSF-Algorithm) for remote sensing (RS) imagery that employs the robust descriptive experiment design (DED) approach, using a graphics processing unit (GPU) as parallel architecture. The achieved performance is significantly greater than initial requirement of two image per second. The performance results are reported in terms of metrics as: number of operations, memory requirements, execution time, and speedup, which show the achieved improvements by the parallel version in comparison with the sequential version of the algorithm.
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Castro-Palazuelos, D., Robles-Valdez, D., Torres-Roman, D. (2014). An Efficient GPU-Based Implementation of the R-MSF-Algorithm for Remote Sensing Imagery. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_125
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DOI: https://doi.org/10.1007/978-3-319-12568-8_125
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12567-1
Online ISBN: 978-3-319-12568-8
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