Ultrasound image quality is degraded because of the presence of speckle, which causes loss of image contrast resolution
and makes the detection of small features difficult. The traditional nonlinear diffusion filtering of speckle reduction with
explicit schemes can achieve desirable results, but they are only stable for very small time steps. Semi-implicit additive
operator splitting (AOS) schemes for nonlinear diffusion are stable for all time size and more efficient than the
traditional explicit schemes. However, the AOS schemes are still inefficient for real time speckle reducing of ultrasound
images. Current graphics processing units (GPUs) offers an opportunity to boost the computation speed of AOS schemes
through high computational power at low cost. In this paper, an optimized GPU framework for AOS schemes is
presented. By using the well-established method of cyclic reduction of tridiagonal systems in our framework, we are able
to implement the AOS schemes on GPU. Experiments from CPU implemented AOS schemes and our GPU based
framework show that our method is about 10 times faster than the CPU implementation. Our presented framework deals
with the local coherence anisotropic diffusion, but it can be generalized to the class of nonlinear diffusion methods which
can be discretized by AOS schemes.
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