Accelerating Translational Image Registration for HDR Images on GPU

2020-10-09
Alpay, Kadir Cenk
Aydemir, Kadir Berkay
Temizel, Alptekin
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
Citation Formats
K. C. Alpay, K. B. Aydemir, and A. Temizel, “Accelerating Translational Image Registration for HDR Images on GPU,” presented at the High performance computing conference, 2020, Ankara, Turkey, 2020, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/78767.