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An Improved Fuzzy Algorithm to Improve Medical Image Contrast

机译:改善医学图像对比度的改进模糊算法

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Noise led from nodes of medical imaging system and underexposure or overexposure will make the image be in a low contrast. In this paper we try to enhance the image contrast with a method of digital image processing. We present an unproved fuzzy algorithmic approach on the basis of the conventional Pas. S. K algorithm. Processed by this improved algorithm, the imperceptible information can be avoided to lose when the planar space of original image is transformed to the fuzzy space. And special experiment has been carried out to demonstrate the effect of this approach applying on the X-ray roentgenoscopy image of animal carotid, which is obtained by a homemade instrument and convert to digital signal with an image-collecting card. We find that both images processed with the conventional algorithm and the improved algorithm can provide more details than the original one. While percent of the zero gray pixels of the image processed with the conventional algorithm is much more (to reach 12.3%) than that with the improved algorithm (6.2%) by analyzing with Visual C++ image process program, indicating a more loss of information caused by the forcible process of making some image elements equal to zero. Thus it can be concluded that the improved algorithm seems to be more distinct than the conventional one.
机译:来自医学成像系统节点的噪声以及曝光不足或曝光过度将导致图像对比度低。在本文中,我们尝试使用数字图像处理方法来增强图像对比度。我们在常规Pas的基础上提出了一种未经验证的模糊算法。 S.K算法。通过该改进算法处理,可以避免将原始图像的平面空间转换为模糊空间时无法感知的信息丢失。并进行了特殊的实验,以证明该方法对动物颈动脉的X射线X射线透视检查图像的效果,该图像是通过自制仪器获得的,并通过图像采集卡转换为数字信号。我们发现,用传统算法和改进算法处理的图像都可以提供比原始图像更多的细节。通过使用Visual C ++图像处理程序进行分析,与常规算法处理后的图像相比,零灰度像素百分比(达到12.3%)要多得多(达到12.3%),这表明造成的信息损失更大通过使某些图像元素等于零的强制过程。因此可以得出结论,改进算法似乎比传统算法更具特色。

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