摘要
随着计算机并行计算技术的快速发展,需要处理的数据量越来越大,提升并行计算的能力成为亟待解决的一个问题。在计算机图像处理的过程中,每一个环节可能都需要大量的计算,提出的C++AMP并行运算可以很好地提高计算机的处理效率。例如在视频监控内容处理时,为了获取到更加清楚的图像信息,通常会将图像放大,然而当图像放大后经常会看到边缘信息不清晰,图像异常模糊。能够获取一个清晰的图像边缘,对于信息的获取就非常重要了。对于视频监控图像模糊难以辨别的情况,提出了基于C++AMP的改进Canny算子的图像边缘信息处理方法。首先介绍了C++AMP的概念,以及现行的Canny算子处理方法,针对现行的Canny算子进行优化,并且对C++AMP并行化实现改进的Canny算子进行研究。然后采用改进梯度幅值的方法对Canny算子进行优化,通过对串行处理和改进Canny算子的并行化处理对比,可以看出并行运算的优势,图像越大,优势越明显,图像越清晰,边缘更多、更加明显,运算的时间也更快。
With the rapid development of parallel computing technology, the amount of data to be processed is also increasing, so the in- crease of parallel computing becomes an urgent problem to be solved. In the processing of computer image,each link may need a lot of computing,and the C++AMP parallel computing can greatly improve the processing efficiency. For example in the surveillance video content processing,in order to get more clear image information, the image will be magnified. However,it will get a edge information af- ter image magnification, not clear and abnormal blur. Therefore, acquiring a clear image edge is much important for information acquisition. For the monitoring image is difficult to identify, we put forward an image edge information processing method of improved Canny operator based on C++ AMP. First we introduce the concept of C++ AMP and the current processing method of Canny operator. The current Canny operator is optimized, and the Canny operator improved by C++AMP parallelization is studied. Then the improved gradient amplitude method is used to optimize the Canny operator. Form the comparison between the serial processing and the parallelization of Canny operator,we can see the advantage of the latter. The advantages arc more obvious when the images are bigger. The edge will be wider and more obvious and the operation will get faster when the images are clearer.
作者
苏锦
马明栋
SU Jin;MA Ming-dong(School of Telecommunications & Information Engineering,Nanjing University of Posts and Telecommunications, Nanjing 210003 ,China)
出处
《计算机技术与发展》
2018年第5期182-186,共5页
Computer Technology and Development
基金
江苏省青年科学基金项目(BK20140868)