Parallel unmixing of remotely sensed hyperspectral images on commodity graphics processing units

نویسندگان

  • Sergio Sánchez
  • Abel Paz
  • Gabriel Martín
  • Antonio J. Plaza
چکیده

Hyperspectral imaging instruments are capable of collecting hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. One of the main problems in the analysis of hyperspectral data cubes is the presence of mixed pixels, which arise when the spatial resolution of the sensor is not enough to separate spectrally distinct materials. Hyperspectral unmixing is one of the most popular techniques to analyze hyperspectral data. It comprises two stages: (i) automatic identification of pure spectral signatures (endmembers) and (ii) estimation of the fractional abundance of each endmember in each pixel. The spectral unmixing process is quite expensive in computational terms, mainly due to the extremely high dimensionality of hyperspectral data cubes. Although this process maps nicely to high performance systems such as clusters of computers, these systems are generally expensive and difficult to adapt to real-time data processing requirements introduced by several applications, such as wildland fire tracking, biological threat detection, monitoring of oil spills, and other types of chemical contamination. In this paper, we develop an implementation of the full hyperspectral unmixing chain on commodity graphics processing units (GPUs). The proposed methodology has been implemented, using the CUDA (compute device unified architecture), and tested on three different GPU architectures: NVidia Tesla C1060, NVidia GeForce GTX 275, and NVidia GeForce 9800 GX2, achieving near real-time unmixing performance in some configurations tested when analyzing two different hyperspectral images, collected over the World Trade Center complex in New York City and the Cuprite mining district in Nevada. Copyright 2011 John Wiley & Sons, Ltd.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Real-time lossy compression of hyperspectral images using iterative error analysis on graphics processing units

Hyperspectral image compression is an important task in remotely sensed Earth Observation as the dimensionality of this kind of image data is ever increasing. This requires on-board compression in order to optimize the donwlink connection when sending the data to Earth. A successful algorithm to perform lossy compression of remotely sensed hyperspectral data is the iterative error analysis (IEA...

متن کامل

Graphics processing unit implementation of JPEG2000 for hyperspectral image compression

Hyperspectral image compression has received considerable interest in recent years due to the enormous data volumes collected by imaging spectrometers for Earth Observation. JPEG2000 is an important technique for data compression, which has been successfully used in the context of hyperspectral image compression, either in lossless and lossy fashion. Due to the increasing spatial, spectral, and...

متن کامل

Use of FPGA or GPU-based architectures for remotely sensed hyperspectral image processing

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...

متن کامل

GPUs versus FPGAs for Onboard Payload Compression of Remotely Sensed Hyperspectral Data

In this paper, we compare field programmable gate arrays (FPGAs) versus graphical processing units (GPUs) in the framework of (lossy) remotely sensed hyperspectral data compression by developing parallel implementations of a spectral unmixing-based compression strategy on both platforms. For the FPGA implementations, we resort to Xilinx hardware devices certified for on-board operation, while f...

متن کامل

Near real-time endmember extraction from remotely sensed hyperspectral data using NVidia GPUs

One of the most important techniques for hyperspectral data exploitation is spectral unmixing, which aims at characterizing mixed pixels. When the spatial resolution of the sensor is not fine enough to separate different spectral constituents, these can jointly occupy a single pixel and the resulting spectral measurement will be a composite of the individual pure spectra. The N-FINDR algorithm ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Concurrency and Computation: Practice and Experience

دوره 23  شماره 

صفحات  -

تاریخ انتشار 2011