Hello academy-lovers!
Our new study is now available on arXiv:
K.C. Alpay, K.B. Aydemir, A. Temizel, “Accelerating Translational Image Registration for HDR Images on GPU”, arXiv:2007.06483, July 2020.
https://arxiv.org/abs/2007.06483
Our paper got accepted for publication in High Performance Computing Conference: BAŞARIM 2020.
It also got invited for submission to Concurrency and Computation: Practice and Experience | Wiley (CCPE) Journal BASARIM2020 Special Issue.
Click here to watch our conference presentation.
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
Hope to see you in the next studies!