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- W2082433146 abstract "On-board real-time processing is highly desirable in airborne detection applications. As the data processinginvolved here is computationally expensive, typically high power multi-rack system is required to achieve real-timedetection. Use of such hardware on-board is often not feasible in airborne applications due to spaceand power constraints. Recently, there has been a lot of interest in the use of Graphics Processing Units(GPUs) for real-time image processing because of their highly parallel architecture, low cost, and compactsize. With the introduction of high level languages like C/CUDA (Nvidia), CTM (ATI), OpenCL, etc., GPUsare enjoying a manifold increase in their adoption for general purpose computation. In this paper we presentGPU bound implementations of image registration and multiband RX anomaly detector. We identify the sub-problems,namely band-to-band registration, phase correlation, feature detection, feature tracking and imagetransformation, that can be efficiently parallelized on the SIMD architecture of the GPU. The results fromexperiments using these implementation are compared against existing implementation written in Matlab andC++." @default.
- W2082433146 created "2016-06-24" @default.
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- W2082433146 date "2010-04-23" @default.
- W2082433146 modified "2023-09-26" @default.
- W2082433146 title "GPU-based processing for airborne detection" @default.
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- W2082433146 doi "https://doi.org/10.1117/12.851492" @default.
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