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arXiv · 2007.06483

Accelerating Translational Image Registration for HDR Images on GPU

Kadir Cenk Alpay·Kadir Berkay Aydemir·Alptekin Temizel
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Abstract

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

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Kadir Cenk Alpay, Kadir Berkay Aydemir, Alptekin Temizel. 2020-07-13. Accelerating Translational Image Registration for HDR Images on GPU. https://arxiv.org/abs/2007.06483

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