Denoising method to dynamic digital X-ray images and its fast implementation
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摘要: 对于X射线动态数字成像系统,为了实现高帧频采集引起的数字摄影(DR,Digital Radiography)图像降质的恢复,采用Anscombe变换将NL-means降噪算法引入到DR图像的降噪中.为了解决NL-means降噪算法计算量大、运算速度慢的问题,利用可编程图形处理单元(GPU,Graphic Processing Unit)并行计算和高速浮点计算特性,将DR图像映射为GPU中的纹理,采用多线程并行计算,使得NL-means算法在GPU中加速执行.实验结果表明,NL-means能够有效抑制动态DR图像噪声.GPU加速方法可以在不损失图像信息的前提下,加速比可达2个数量级以上,满足了实时降噪的要求.
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关键词:
- 数字摄影图像降噪 /
- NL-means /
- Anscombe变换 /
- 图形处理单元
Abstract: For the dynamic digital X-ray imaging system, in order to solve the degradation of DR (Digital Radiography) image quality, NL-means algorithm was introduced for the DR image denoising by using the Anscombe transform. In order to solve its complex calculation and time-consuming problem, GPU (Graphic Processing Unit) was used for its high parallel computing and fast floating-point calculation abilities. During implementation, the original noisy DR image was mapped to the GPU's texture and each thread calculated one pixel. By using its multi-threads, the NL-means algorithm could be effectively accelerated in GPU. The results show that the NL-means denoising method can effectively restrain the noise of dynamic DR images, and the acceleration with GPU can speed up more than 2 orders of magnitude without the loss of resolution, which met the satisfaction of real-time denoising.
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