Accelerating Translational Image Registration for HDR Images on GPU

Date

2020-10-09

Author

Alpay, Kadir Cenk
Temizel, Alptekin

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High Dynamic Range (HDR) images are generated using multiple exposures of a scene. When a hand-held camera is used to capture a static scene, these images need to be aligned by globally shifting each image in both dimensions. For a fast and robust alignment, the shift amount is commonly calculated using Median Threshold Bitmaps (MTB) and creating an image pyramid. In this study, we optimize these computations using a parallel processing approach utilizing GPU. Experimental evaluation shows that the proposed implementation achieves a speed-up of up to 6.24 times over the baseline multi-threaded CPU implementation on the alignment of one image pair. The source code is available at https://github.com/kadircenk/WardMTBCuda

URI

https://hdl.handle.net/11511/78767

Conference Name

High performance computing conference, 2020

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

K. C. Alpay and A. Temizel, “Accelerating Translational Image Registration for HDR Images on GPU,” presented at the High performance computing conference, 2020, Ankara, Türkiye, 2020, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/78767.