Scene Matching Techniques Using Satellite Imagery Data

A. A. Shahin
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Abstract

The problem of scene matching is a challenging problem in the field of image processing and pattern recognition. Therefore, it is modeled and its influencing factors are analyzed. According to sources, influence factors can be catalogued into three types: 1- changes of scenes 2- changes of image conditions 3- changes of sensors. For each factor, its mechanism is discussed. Given a pictorial description of a region of a scene, it is desired to determine which region in another scene is similar. The most efficient algorithms for scene matching are discussed. Those are the sequential hierarchical scenes matching algorithms for grey-scale and binary images and the two-stage template-matching algorithm. Experimental results are presented for matching satellite images of AI-Minea (EGYPT) and Montana (USA) using those approaches. The results prove efficiency and success in reaching the best match location with minimum required computations. A comment on the results is presented as well as a comparison between the applied methods.
使用卫星图像数据的场景匹配技术
场景匹配问题是图像处理和模式识别领域的一个具有挑战性的问题。为此,对其进行建模,并分析其影响因素。根据来源,影响因素可分为三类:1-场景的变化2-图像条件的变化3-传感器的变化。对每个因素的作用机理进行了探讨。给定场景的一个区域的图形描述,希望确定另一个场景中的哪个区域是相似的。讨论了最有效的场景匹配算法。分别是灰度和二值图像的顺序分层场景匹配算法和两阶段模板匹配算法。给出了利用这些方法对埃及的AI-Minea和美国蒙大拿州的卫星图像进行匹配的实验结果。结果表明,该方法能够以最少的计算量获得最佳匹配位置。对结果进行了评论,并对应用的方法进行了比较。
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