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Bayes Filter based Jitter Noise Removal in Shape Recovery from Image Focus

机译:基于贝叶斯过滤器的抖动噪声去除图像焦点形状恢复

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摘要

Shape from Focus (SFF) is a passive technique that is used to recover the 3D shape of an object using a series of images with different focus settings. When 2D image sequences are obtained with a specific sampling step size along the optical axis in SFF, mechanical vibrations occur in the position of each image frame. These mechanical vibrations, also referred as jitter noise, affect the accuracy of 3D shape recovery. In this manuscript, the jitter noise and focus curves are modeled as Gaussian function. This is followed by a Bayes filter application, designed to reduce the jitter noise. The filter is applied to each image frame in the Gaussian approximation of the focus curve. The proposed method is experimented by using synthetic and real objects to show performance improvement. (C) 2019 Society for Imaging Science and Technology.
机译:来自焦点(SFF)的形状是一种被动技术,用于使用具有不同焦点设置的一系列图像来恢复对象的3D形状。 当用沿着SFF中的光轴沿着光轴获得2D图像序列时,在每个图像帧的位置发生机械振动。 这些机械振动,也称为抖动噪声,影响3D形状恢复的准确性。 在该稿件中,抖动噪声和焦点曲线被建模为高斯函数。 随后是贝叶斯过滤器应用,旨在减少抖动噪声。 滤波器应用于聚焦曲线的高斯近似的每个图像帧。 通过使用合成和真实物体来实验该方法以显示性能改进。 (c)2019年成像科技协会。

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