Performance Evaluation of Pansharpening Methods on GPU for RASAT Images

Date

2015-06-19

Author

Acikgoz, Ibrahim Serdar
Teke, Mustafa
KUTBAY, UĞURHAN
HARDALAÇ, FIRAT

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Turkey is among the countries which could develop earth observation satellites. RASAT and Gokturk-2 satellites are still operational and continuously acquire images of the Earth. Their images are processed before sharing with end users. Pansharpening, at which high resolution pan and low resolution multi-spectral images are fused, is an important step in image processing chain. As the resolution and number of images increase, pansharpening of satellite images take considerable amount of time. Multithread programming and General Purpose GPU (GPGPU) programming implementation improve performance of image processing applications, where most operations carried out on individual pixels. In this paper, we compared pansharpening applications and their CPU and GPU implementations for RASAT images. GPU implementations of pansharpening algorithms provides 20-25 times speed-up compared to CPU implementations.

Subject Keywords

RASAT, Image processing, Pansharpening, GPU, CUDA

URI

https://hdl.handle.net/11511/67331

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Citation Formats

I. S. Acikgoz, M. Teke, U. KUTBAY, and F. HARDALAÇ, “Performance Evaluation of Pansharpening Methods on GPU for RASAT Images,” 2015, p. 283, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67331.