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Quaternion-Based Improved Artificial Bee Colony Algorithm for Color Remote Sensing Image Edge Detection

机译:基于四元的偏远图像边缘检测改进的人工蜂菌落算法

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摘要

As the color remote sensing image has the most notable features such as huge amount of data, rich image details, and the containing of too much noise, the edge detection becomes a grave challenge in processing of remote sensing image data. To explore a possible solution to the urgent problem, in this paper, we first introduced the quaternion into the representation of color image. In this way, a color can be represented and analyzed as a single entity. Then a novel artificial bee colony method named improved artificial bee colony which can improve the performance of conventional artificial bee colony was proposed. In this method, in order to balance the exploration and the exploitation, two new search equations were presented to generate candidate solutions in the employed bee phase and the onlookers phase, respectively. Additionally, some more reasonable artificial bee colony parameters were proposed to improve the performance of the artificial bee colony. Then we applied the proposed method to the quaternion vectors to perform the edge detection of color remote sensing image. Experimental results show that our method can get a better edge detection effect than other methods.
机译:由于颜色遥感图像具有大量的数据,丰富的图像细节和含有太多噪声的最值得注意的功能,因此边缘检测成为处理遥感图像数据的严重挑战。为了探讨迫切问题的可能解决方案,在本文中,我们首先将四元数引入彩色图像的表示。以这种方式,可以将颜色表示和分析为单个实体。然后提出了一种新的人造蜜蜂菌落方法,称为改进的人造蜂菌落,这提出了可以提高常规人造蜂菌落的性能。在该方法中,为了平衡探索和开发,提出了两个新的搜索方程,以便分别在所采用的BEE相和旁观者阶段生成候选解决方案。另外,提出了一些更合理的人造蜜蜂参数来改善人造蜂菌落的性能。然后,我们将所提出的方法应用于四元数向量,以执行彩色遥感图像的边缘检测。实验结果表明,我们的方法可以获得比其他方法更好的边缘检测效果。

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