基于自适应梯度阈值的遥感图像改进SUSAN角点检测算法

Wei He, Xiaolian Deng
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引用次数: 7

摘要

遥感图像配准在图像处理中起着重要的作用。准确的角点检测是图像配准的关键。提出了一种改进的基于自适应梯度阈值的SUSAN角点检测算法。自动保证灰度阈值是新算法的关键。首先,对传统的SUSAN原理和新算法进行了详细的讨论。然后,利用ASTER遥感数据,利用MATLAB 7.0软件对上述两种方法进行了测试。实验结果表明,该算法具有较强的适应性,具有较好的应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Modified SUSAN Corner Detection Algorithm Based on Adaptive Gradient Threshold for Remote Sensing Image
Remote Sensing image registration plays an important role in image processing. The exact corner detection is vital to image registration. A modified SUSAN corner detection algorithm based on adaptive gradient threshold is presented. Ensuring the gray threshold automatically is the key of the new algorithm. First, the Traditional SUSAN principle and the new algorithm are discussed carefully. Then, testing the two methods that have been mentioned with the software of MATLAB 7.0 using the ASTER remote sensing data. Experimental result indicates that the proposed algorithm is more adaptable and has better applicable value.
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