Developing a portable GPU library for hyperspectral image processing

Gabriel J. Pérez-Irizarry; Francisco De La Cruz-Sanchez; Brian A. Landrón-Rivera; Nayda G. Santiago; Miguel Velez-Reyes

doi:10.1117/12.920499

24 May 2012 Developing a portable GPU library for hyperspectral image processing

Gabriel J. Pérez-Irizarry, Francisco De La Cruz-Sanchez, Brian A. Landrón-Rivera, Nayda G. Santiago, Miguel Velez-Reyes

Author Affiliations +

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 839017 (2012) https://doi.org/10.1117/12.920499
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

The increasing volume of data produced by hyperspectral image sensors have forced researches and developers to seek out new and more ecient ways of analyzing the data as quick as possible. Medical, scientic, and military applications present performance requirements for tools that perform operations on hyperspectral sensor data. By providing a hyperspectral image analysis library, we aim to accelerate hyperspectral image application development. Development of a cross-platform library, Libdect, with GPU support for hyperspectral image analysis is presented. Coupling library development with ecient hyperspectral algorithms escalates into a signicant time invest- ment in many projects or prototypes. Provided a solution to these issues, developers can implement hyperspectral image analysis applications in less time. Developers will not be focused on implementing target detection code and potential issues related to platform or GPU architecture dierences. Libdect's development team counts with previously implemented detection algorithms. By utilizing proven tools, such as CMake and CTest, to develop Libdect's infrastructure, we were able to develop and test a prototype library that provides target detection code with GPU support on Linux platforms. As a whole, Libdect is an early prototype of an open and documented example of Software Engineering practices and tools. They are put together in an eort to increase developer productivity and encourage new developers into the eld of hyperspectral image application development.

Citation Download Citation

Gabriel J. Pérez-Irizarry, Francisco De La Cruz-Sanchez, Brian A. Landrón-Rivera, Nayda G. Santiago, and Miguel Velez-Reyes "Developing a portable GPU library for hyperspectral image processing", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839017 (24 May 2012); https://doi.org/10.1117/12.920499

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KEYWORDS

Hyperspectral imaging

Sensors

Prototyping

Algorithm development

Detection and tracking algorithms

Software development

Image analysis

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