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Images corrupted by gaussian noise enhancement via piecewise linear models

机译:通过分段线性模型被高斯噪声增强损坏的图像

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Noise having Gaussian-like distribution is very often encountered during image acquisition. Tranditional enhancement methods (space domain and frequency domain) can reduce noise, but also are easy to produce blurred edge. So 5-parameter PWL nonlinear transformation is used to enhance image and reduce noise. A satisfactory combination of image enhancement and noise attenuation can be achieved by different parameter settings. Results dealing with images with different noise variance show that the method yields a very effective enhancement of the image data.
机译:在图像采集期间,经常会遇到具有高斯样分布的噪声。传统的增强方法(空间域和频域)可以减少噪声,但也容易产生模糊边缘。因此,使用五参数PWL非线性变换来增强图像并降低噪声。通过不同的参数设置可以实现图像增强和噪声衰减的令人满意的组合。处理具有不同噪声方差的图像的结果表明,该方法可以非常有效地增强图像数据。

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