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A Laplacian based image filtering using switching noise detector

机译:使用开关噪声检测器的基于Laplacian的图像滤波

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摘要

This paper presents a Laplacian-based image filtering method. Using a local noise estimator function in an energy functional minimizing scheme we show that Laplacian that has been known as an edge detection function can be used for noise removal applications. The algorithm can be implemented on a 3x3 window and easily tuned by number of iterations. Image denoising is simplified to the reduction of the pixels value with their related Laplacian value weighted by local noise estimator. The only parameter which controls smoothness is the number of iterations. Noise reduction quality of the introduced method is evaluated and compared with some classic algorithms like Wiener and Total Variation based filters for Gaussian noise. And also the method compared with the state-of-the-art method BM3D for some images. The algorithm appears to be easy, fast and comparable with many classic denoising algorithms for Gaussian noise.
机译:本文提出了一种基于拉普拉斯算子的图像滤波方法。在能量函数最小化方案中使用局部噪声估计器函数,我们表明被称为边缘检测函数的拉普拉斯算子可以用于噪声消除应用。该算法可以在3x3窗口上实现,并可以根据迭代次数轻松调整。图像去噪简化为像素值的减少,而像素值的相关拉普拉斯值由局部噪声估计器加权。控制平滑度的唯一参数是迭代次数。对引入的方法的降噪质量进行了评估,并与一些经典算法(例如针对高斯噪声的Wiener和基于总变化的滤波器)进行了比较。并且该方法与某些图像的最新方法BM3D进行了比较。该算法看起来简单,快速,并且可与许多经典的高斯噪声去噪算法相提并论。

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