A GPU Accelerated Local Polynomial Approximation Algorithm for Efficient Denoising of MR Images

  • Artur KlepaczkoEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 226)


This paper presents a parallelized implementation of the Local Polynomial Approximation algorithm targetted at CUDA-enabled GPU hardware. Although the application area of LPA in the image processing domain is very wide, here the focus is put on magnetic resonance image de-noising. In this case, LPA serves as a pre-processing step in the method based on Shape-Adaptive Discrete Cosine Transform. It is shown, how the designed efficient implementation of LPA substantially reduces the execution time of SA-DCT.


Shared Memory Global Memory Thread Block Streaming Multiprocessor Rician Noise 
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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Institute of ElectronicsLodz University of TechnologyLodzPoland

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