Developing a portable GPU library for hyperspectral image processing

The increasing volume of data produced by hyperspectral image sensors have forced researches and developers to seek out new and more efficient ways of analyzing the data as quick as possible. Medical, scientific, 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 efficient hyperspectral algorithms escalates into a significant time investment 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 differences. 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 effort to increase developer productivity and encourage new developers into the field of hyperspectral image application development.