Accelerating Space Variant Gaussian Filtering on Graphics Processing Unit

机译：在图形处理单元上加速空间变异高斯滤波

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摘要

In this paper we examine the performance advantages of using a GPU to execute the space variant Gaussian filtering. Our results show that the straightforward convolution GPU implementation obtains up to 8 times better performance than the best recursive algorithm (the Deriche's filter) executed on a CPU, for useful maximum σ values. GPUs have turned out a useful option to obtain high execution performance, specially due to the emergence of high level languages for graphics hardware.

机译：在本文中，我们研究了使用GPU执行空间变量高斯滤波的性能优势。我们的结果表明，对于有用的最大σ值，直接的卷积GPU实现比在CPU上执行的最佳递归算法（Deriche滤波器）的性能高出8倍。 GPU已成为获得高执行性能的有用选择，特别是由于图形硬件的高级语言的出现。

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《International Conference on Computer Aided Systems Theory(EUROCAST 2007); 20070212-16; Las Palmas de Gran Canaria(ES)》|2007年|P.984-991|共8页
会议地点 Las Palmas de Gran Canaria(ES)
作者
Roman Dudek; Carmelo Cuenca; Prancisca Quintana;
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Departamento de Informatica y Sistemas Universidad de Las Palmas de Gran Canaria, Spain;

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原文格式 PDF
正文语种 eng
中图分类机器辅助技术;
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Accelerating Space Variant Gaussian Filtering on Graphics Processing Unit

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