Optimized GPU Framework for Speckle Reduction Using Histogram Matching and Region Growing
Comput. Sci. Coll., Sichuan Univ., Chengdu, China
4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2010
@conference{shi2010optimized,
title={Optimized GPU Framework for Speckle Reduction Using Histogram Matching and Region Growing},
author={Shi, D. and Li, X. and Liu, D.C.},
booktitle={Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on},
pages={1–4},
issn={2151-7614},
organization={IEEE},
year={2010}
}
A GPU framework for ultrasound speckle reduction by region growing based on local statistics extracted from the histogram shape is presented. The required image processing is computationally intensive, involving histogram calculation, region growing, box filtering using different sizes of windows, and more. In this paper, we describe the use of a graphics processing unit for implementing image processing algorithms for speckle reduction that achieves a frame rate of 28 fps for the 512×512 image, about 81 times faster than the CPU implementation. Testing results from GPU and CPU are compared in terms of visual image quality and program runtime from different image sizes.
May 11, 2011 by hgpu
