GPU-based processing for airborne detection

Dheeraj Singiresu; Sanjeev Agarwal; Shivakar Vulli; Harish Ramakrishnan

doi:10.1117/12.851492

29 April 2010 GPU-based processing for airborne detection

Dheeraj Singiresu, Sanjeev Agarwal, Shivakar Vulli, Harish Ramakrishnan

Proceedings Volume 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV; 766427 (2010) https://doi.org/10.1117/12.851492
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

On-board real-time processing is highly desirable in airborne detection applications. As the data processing involved here is computationally expensive, typically high power multi-rack system is required to achieve real-time detection. Use of such hardware on-board is often not feasible in airborne applications due to space and 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 compact size. With the introduction of high level languages like C/CUDA (Nvidia), CTM (ATI), OpenCL, etc., GPUs are enjoying a manifold increase in their adoption for general purpose computation. In this paper we present GPU 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 image transformation, that can be efficiently parallelized on the SIMD architecture of the GPU. The results from experiments using these implementation are compared against existing implementation written in Matlab and C++.

Citation Download Citation

Dheeraj Singiresu, Sanjeev Agarwal, Shivakar Vulli, and Harish Ramakrishnan "GPU-based processing for airborne detection", Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 766427 (29 April 2010); https://doi.org/10.1117/12.851492

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