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2009 International Conference on Environmental Science and Information Application Technology
An Accelerated IHS Transform Fusion of Remote Sensing Image Data Based on GPU
Wuhan, China
July 04-July 05
ISBN: 978-0-7695-3682-8
| ASCII Text | x | ||
| Jun Lu, Baoming Zhang, "An Accelerated IHS Transform Fusion of Remote Sensing Image Data Based on GPU," Environmental Science and Information Application Technology, International Conference on, vol. 1, pp. 492-496, 2009 International Conference on Environmental Science and Information Application Technology, 2009. | |||
| BibTex | x | ||
| @article{ 10.1109/ESIAT.2009.117, author = {Jun Lu and Baoming Zhang}, title = {An Accelerated IHS Transform Fusion of Remote Sensing Image Data Based on GPU}, journal ={Environmental Science and Information Application Technology, International Conference on}, volume = {1}, year = {2009}, isbn = {978-0-7695-3682-8}, pages = {492-496}, doi = {http://doi.ieeecomputersociety.org/10.1109/ESIAT.2009.117}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Environmental Science and Information Application Technology, International Conference on TI - An Accelerated IHS Transform Fusion of Remote Sensing Image Data Based on GPU SN - 978-0-7695-3682-8 SP492 EP496 A1 - Jun Lu, A1 - Baoming Zhang, PY - 2009 KW - GPU KW - RIT KW - MRT KW - Fragmentshader VL - 1 JA - Environmental Science and Information Application Technology, International Conference on ER - | |||
In this paper we designed a remote sensing image data fusion algorithm on GPU (Graphics Processing Unit) using the programmability of GPU which is a parallel vector processor. Both of the forward IHS and inverse IHS transform computation were mapped into GPU. We realized parallel rendering and output of the three components of the IHS, and the inverse IHS transformation using RTT (Render To Texture) and MTR (Multiple Render Targets) method to speed up the computation. The result shows that this algorithm on GPU is much faster than the previous CPU-based IHS transforming algorithm in the case of large data. And with the fusion images getting bigger the advantage of the velocity is more obvious in GPU implementation.
Index Terms:
GPU, RIT, MRT, Fragmentshader
Citation:
Jun Lu, Baoming Zhang, "An Accelerated IHS Transform Fusion of Remote Sensing Image Data Based on GPU," esiat, vol. 1, pp.492-496, 2009 International Conference on Environmental Science and Information Application Technology, 2009
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