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A Method of Total Variation to Remove the Mixed Poisson-Gaussian Noise1

机译:总变分消除混合泊松-高斯噪声的方法1

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摘要

There are many modern devices are used to create digital images. These devices use optical effects to create images. Therefore, the image quality depends on quality of optical sensors. Because of the limits of technology, these sensors cannot reconstruct the images perfectly, and always include some defects. One from these defects is noise. The noise reduces image quality and result of image processing. The image noises can be classified into some types: Gaussian noise, Poisson noise, speckle noise and so on. Depending on particular noises, we have efficient methods to remove them. There is no existing a universal method to remove all noises effectively. In this paper, we proposed a method to remove a noise that is popular in biomedicine. This noise can be considered as a combination of Gaussian and Poisson noises. Our method is based on the total variation of an image intensity (brightness) function.
机译:有许多现代设备用于创建数字图像。这些设备使用光学效果创建图像。因此,图像质量取决于光学传感器的质量。由于技术的限制,这些传感器无法完美地重建图像,并且始终存在一些缺陷。这些缺陷之一就是噪声。噪点会降低图像质量和图像处理结果。图像噪声可以分为几种类型:高斯噪声,泊松噪声,斑点噪声等。根据特定的噪音,我们有有效的方法将其消除。目前还没有一种通用的方法可以有效地消除所有噪音。在本文中,我们提出了一种消除生物医学中流行的噪声的方法。可以将这种噪声视为高斯和泊松噪声的组合。我们的方法基于图像强度(亮度)函数的总变化。

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