Modulation transfer function and noise measurement using neural networks

J. Delvit, D. Léger, S. Roques, C. Valorge
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引用次数: 3

Abstract

In the context of Earth observation satellites such as SPOT or IKONOS, it is important to measure the modulation transfer function (MTF) and the noise in order to quantify the quality of the imaging system. This measurement is useful to decide to focus the telescope or to make a deconvolution filter whose purpose is to enhance image contrast. This paper presents a univariant MTF and noise measurement method using non specific views. It is a particular application of a general approach of image quality assessment. The method presented in this paper is based on artificial neural network (ANN) use. The ANN learns how to recognize MTF and noise from known images, and the neural network is able, after the learning step, to assess the MTF and the noise from unknown images.
调制传递函数与神经网络噪声测量
在SPOT或IKONOS等对地观测卫星中,为了量化成像系统的质量,测量调制传递函数(MTF)和噪声是很重要的。这一测量对于决定望远镜的焦距或制作反卷积滤波器以增强图像对比度是有用的。本文提出了一种基于非特定视图的无变MTF和噪声测量方法。它是一般图像质量评估方法的一个特殊应用。本文提出的方法是基于人工神经网络(ANN)的应用。人工神经网络学习如何从已知图像中识别MTF和噪声,并且神经网络能够在学习步骤之后评估未知图像中的MTF和噪声。
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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