Adaptive Texture Representation Methods for Automatic Target Recognition

Adaptive Texture Representation Methods for Automatic Target Recognition
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自动目标识别的自适应纹理表示方法

DOI：
10.5244/c.13.44
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发表时间：
1999
期刊：
--
影响因子：
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通讯作者：
J. Kittler
J. Kittler
中科院分区：
--
文献类型：
--
作者：
K. Messer;D. Ridder;J. Kittler

文献摘要

被引文献

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自动目标识别（ATR）是一个要求很高的应用，需要从一系列图像的噪声背景中分离出目标。本文提出了两种自适应的方法来描述这样的背景，这是基于主成分和独立成分分析的采样图像块。结合特征选择和异常值检测技术，它们使ATR系统能够适应某些背景，并将图像中的非标准元素识别为目标。所提出的方法进行了比较，与一个标准的基于小波的方法，并表现出更好地执行一个困难的图像序列。
Automatic Target Recognition (ATR) is a demanding application that requires separation of targets from a noisy background in a sequence of images. In this paper, two adaptive methods for describing such a background are proposed which are based on Principal and Independent Component Analysis of sampled image patches. Coupled together with feature selection and outlier detection techniques they enable the ATR system to adapt to certain backgrounds and identify non-standard elements in the images as targets. The methods proposed are compared with a standard wavelet-based approach and are shown to perform somewhat better on a difficult image sequence.