论文标题
从灰度医学图像中删除多噪声的平行混合技术
A Parallel Hybrid Technique for Multi-Noise Removal from Grayscale Medical Images
论文作者
论文摘要
医学成像是用于为临床目的创建人体或部分部分图像的技术。医疗图像总是大小较大，并且通常同时被单个或多个噪声类型损坏，这是由于各种原因，这两个原因是向平行图像处理迈出的触发因素，以找到图像删除技术的替代方案。本文提出了一个平行的混合过滤器实现，用于灰度医疗图像降价。杂交是在自适应中值和维纳过滤器之间的。在自适应中值过滤器上实现并行化以克服邻里操作的延迟，使用MATLAB 2013a支持的隐式并行性。该实现在2.5 MB大小的图像上进行了测试，该图像分为2、4和8分区；在时间方面给出了提议的实施与顺序实施之间的比较。因此，将每个情况分配给等于其分区数的线程数时，它们的时间最佳。此外，计算算法的速度和效率，它们显示出测量的增强。
Medical imaging is the technique used to create images of the human body or parts of it for clinical purposes. Medical images always have large sizes and they are commonly corrupted by single or multiple noise type at the same time, due to various reasons, these two reasons are the triggers for moving toward parallel image processing to find alternatives of image de-noising techniques. This paper presents a parallel hybrid filter implementation for gray scale medical image de-noising. The hybridization is between adaptive median and wiener filters. Parallelization is implemented on the adaptive median filter to overcome the latency of neighborhood operation, parfor implicit parallelism powered by MatLab 2013a is used. The implementation is tested on an image of 2.5 MB size, which is divided into 2, 4 and 8 partitions; a comparison between the proposed implementation and sequential implementation is given, in terms of time. Thus, each case has the best time when assigned to number of threads equal to the number of its partitions. Moreover, Speed up and efficiency are calculated for the algorithm and they show a measured enhancement.
