Template matching for noisy images

Sergey Shaydullin, Andrey Turkin, Nikolay Chelyshev
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Abstract

In many applications of computer vision one must deal with images that are distorted by noise which level cannot be estimated exactly. In this work we discuss a template matching framework which uses optimal nonlinear distortion-tolerant filtering technique and can be applied for noisy images. In this paper we assess the accuracy of this framework under conditions of uncertainty in level of noise.
模板匹配噪声图像
在计算机视觉的许多应用中,必须处理被噪声扭曲的图像,这些噪声的电平无法准确估计。在本工作中,我们讨论了一种模板匹配框架,该框架采用最优非线性容忍失真滤波技术,可用于噪声图像。在本文中,我们在噪声水平不确定的条件下评估了该框架的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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