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A new image fusion strategy based on target segmentaion

机译:基于目标分割的图像融合新策略

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By analyzing the characteristics of target in multi spectral image and panchromatic image, a new fusion strategy based on target segmentation is proposed to fuse multi spectral image and panchromatic image. Firstly, Hue-Saturation-Intensity (HSI) transform is performed on the multi spectral image. Secondly, the intensity component by HSI transform is segmented by the expectation maximization (EM) algorithm and the panchromatic image is segmented by fuzzy C means (FCM) clustering algorithm, and obtains the better target area, followed by effective filling of the target area to get the new intensity component. Finally, the new fusion image is obtained by inverse HSI transform. Compared with the traditional HSI method, experiment results shows that the proposed strategy not only increases information entropy and average gradient of fusion image, but also decreases spectral bias index. Therefore, the proposed strategy is better than traditional HSI method. It not only enhances spatial resolution of fusion image and obtains detailed and feature information, but also preserves spectral information of the original multi-spectral image well.
机译:通过分析多光谱图像和全色图像中目标的特性,提出了一种基于目标分割的融合策略,将多光谱图像和全色图像融合。首先,对多光谱图像执行色相饱和度(HSI)变换。其次,通过期望最大化算法对HSI变换的强度分量进行分割,并通过模糊C均值聚类算法对全色图像进行分割,以获得更好的目标区域,然后对目标区域进行有效填充获得新的强度分量。最后,通过逆HSI变换获得新的融合图像。实验结果表明,与传统的HSI方法相比,该方法不仅增加了信息熵和融合图像的平均梯度,而且降低了光谱偏差指数。因此,所提出的策略优于传统的HSI方法。它不仅提高了融合图像的空间分辨率,获得了详细的特征信息,而且很好地保留了原始多光谱图像的光谱信息。

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