دانلود مقاله ISI انگلیسی شماره 81347
ترجمه فارسی عنوان مقاله

استفاده از FPGA و یا معماری مبتنی بر GPU برای پردازش تصویر فراطیفی سنجش از راه دور

عنوان انگلیسی
Use of FPGA or GPU-based architectures for remotely sensed hyperspectral image processing
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
81347 2013 15 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Integration, the VLSI Journal, Volume 46, Issue 2, March 2013, Pages 89–103

ترجمه کلمات کلیدی
تصویربرداری فراطیفی؛ شتاب دهنده سخت افزار؛ FPGAs - GPUs؛ تجربه توسعه نرم افزار
کلمات کلیدی انگلیسی
Hyperspectral imaging; Hardware accelerators; FPGAs; GPUs; Application development experience
پیش نمایش مقاله
پیش نمایش مقاله  استفاده از FPGA و یا معماری مبتنی بر GPU برای پردازش تصویر فراطیفی سنجش از راه دور

چکیده انگلیسی

Hyperspectral imaging is a growing area in remote sensing in which an imaging spectrometer collects hundreds of images (at different wavelength channels) for the same area on the surface of the Earth. Hyperspectral images are extremely high-dimensional, and require advanced on-board processing algorithms able to satisfy near real-time constraints in applications such as wildland fire monitoring, mapping of oil spills and chemical contamination, etc. One of the most widely used techniques for analyzing hyperspectral images is spectral unmixing, which allows for sub-pixel data characterization. This is particularly important since the available spatial resolution in hyperspectral images is typically of several meters, and therefore it is reasonable to assume that several spectrally pure substances (called endmembers in hyperspectral imaging terminology) can be found within each imaged pixel. In this paper we explore the role of hardware accelerators in hyperspectral remote sensing missions and further inter-compare two types of solutions: field programmable gate arrays (FPGAs) and graphics processing units (GPUs). A full spectral unmixing chain is implemented and tested in this work, using both types of accelerators, in the context of a real hyperspectral mapping application using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). The paper provides a thoughtful perspective on the potential and emerging challenges of applying these types of accelerators in hyperspectral remote sensing missions, indicating that the reconfigurability of FPGA systems (on the one hand) and the low cost of GPU systems (on the other) open many innovative perspectives toward fast on-board and on-the-ground processing of remotely sensed hyperspectral images.