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Proceedings Paper

Abundance estimation algorithms using NVIDIA CUDA technology
Author(s): David González; Christian Sánchez; Ricardo Veguilla; Nayda G. Santiago; Samuel Rosario-Torres; Miguel Vélez-Reyes
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Paper Abstract

Spectral unmixing of hyperspectral images is a process by which the constituent's members of a pixel scene are determined and the fraction of the abundance of the elements is estimated. Several algorithms have been developed in the past in order to obtain abundance estimation from hyperspectral data, however, most of them are characterized by being highly computational and time consuming due to the magnitude of the data involved. In this research we present the use of Graphic Processing Units (GPUs) as a computing platform in order to reduce computation time related to abundance estimation for hyperspectral images. Our implementation was developed in C using NVIDIA(R) Compute Unified Device Architecture (CUDATM). The recently introduced CUDA platform allows developers to directly use a GPU's processing power to perform arbitrary mathematical computations. We describe our implementation of the Image Space Reconstruction Algorithm (ISRA) and Expectation Maximization Maximum Likelihood (EMML) algorithm for abundance estimation and present a performance comparison against implementations using C and Matlab. Results show that the CUDA technology produced results around 10 times better than the fastest implementation done on previous platforms.

Paper Details

Date Published: 11 April 2008
PDF: 9 pages
Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69661E (11 April 2008); doi: 10.1117/12.777890
Show Author Affiliations
David González, Univ. of Puerto Rico at Mayagüez (United States)
Christian Sánchez, Univ. of Puerto Rico at Mayagüez (United States)
Ricardo Veguilla, Univ. of Puerto Rico at Mayagüez (United States)
Nayda G. Santiago, Univ. of Puerto Rico at Mayagüez (United States)
Samuel Rosario-Torres, Univ. of Puerto Rico at Mayagüez (United States)
Miguel Vélez-Reyes, Univ. of Puerto Rico at Mayagüez (United States)


Published in SPIE Proceedings Vol. 6966:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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