Title: Accelerating Discrete Wavelet Transforms on GPUs,
Abstract: 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.