Recursive Orthogonal Vector Projection for Hyperspectral Image Abundance Estimation Based on GUP

Chunyan Yu, Jin Huang, Meiping Song, Dong An, Chein I. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Hyperspectral remote sensing data contain more material information for each endmember due to the complexity of the natural object and the limitation of spatial resolution, resulting in the existence of a large number of mixed pixels, which increases the difficulty of data analysis. Abundance estimation is one of the most important topics in hyperspectral unmixing, it can be used to analyze the proportion of mixed pixels accurately. In order to improve the processing speed of hyperspectral image abundance estimation, in this paper, the parallel mode of Recursive Orthogonal Vector Projection (ROVP) algorithm based on NVIDIA's graphic processing unit (GPU) is proposed. The ROVP-C (ROVP-on-CUDA) algorithm based on CPU / GPU heterogeneous system and the ROVP-L (ROVP-on- Library) algorithm based on CUBLAS (CUDA Basic Linear Algebra Subprograms) library are designed and implemented. The experimental results showed that these two algorithms have achieved obvious speed-up ratio compared with the traditional serial algorithms, and it showed that GPU has a great advantage in the field of estimating the hyperspectral abundance.

Original languageEnglish
Title of host publication2018 9th Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781728115818
DOIs
Publication statusPublished - 2018 Sept
Event9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2018 - Amsterdam, Netherlands
Duration: 2018 Sept 232018 Sept 26

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume2018-September
ISSN (Print)2158-6276

Conference

Conference9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2018
Country/TerritoryNetherlands
CityAmsterdam
Period18-09-2318-09-26

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing

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