Accelerating Discrete Wavelet Transforms on GPUs

David Barina, Michal Kula, Michal Matysek, Pavel Zemcik
Faculty of Information Technology, Brno University of Technology, Czech Republic
arXiv:1705.08266 [cs.CV], (18 May 2017)


   title={Accelerating Discrete Wavelet Transforms on GPUs},

   author={Barina, David and Kula, Michal and Matysek, Michal and Zemcik, Pavel},






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The two-dimensional discrete wavelet transform has a huge number of applications in image-processing techniques. Until now, several papers compared the performance of such transform on graphics processing units (GPUs). However, all of them only dealt with lifting and convolution computation schemes. In this paper, we show that corresponding horizontal and vertical lifting parts of the lifting scheme can be merged into non-separable lifting units, which halves the number of steps. We also discuss an optimization strategy leading to a reduction in the number of arithmetic operations. The schemes were assessed using the OpenCL and pixel shaders. The proposed non-separable lifting scheme outperforms the existing schemes in many cases, irrespective of its higher complexity.
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