Abstract
One of the stages of the analysis of satellite images is given by a classification based on the Markov Random Fields (MRF) method. It is possible to find in literature several packages to carry out this analysis, and of course the classification tasks. One of them is the Orfeo Tool Box (OTB). The analysis of satellite images is an expensive computational task requiring real time execution or automatization. In order to reduce the execution time spent on the analysis of satellite images, parallelism techniques can be used. Currently, Graphics Processing Units (GPUs) are becoming a good choice to reduce the execution time of several applications at a low cost. In this paper, the author presents a GPU-based classification using MRF from the sequential algorithm that appears in the OTB package. The experimental results show a spectacular reduction of the execution time for the GPU-based algorithm, up to 225 times faster than the sequential algorithm included in the OTB package. Moreover, this result is also observed in the total power consumption, which is reduced by a significant amount.
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