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Remote sensing image fusion based on fuzzy theory in pixel level and assessing the quality of resulting images

机译:基于模糊理论在像素级别的遥感图像融合,评估结果图像质量

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The technology of image fusion now has been used in the process of remote sensing data. It can integrate the information from multi-sensor data so as to complement the shortage of single sensor image, then more suitable for the purpose of human visual perception, computer-aided object detection, and target recognition. Currently, there are many methods of image fusion we can get from other researcher's study, but these methods of image fusion have some disadvantages. This paper presented the approach of image fusion in pixel level with the fuzzy theory, the source of data used in this paper come from QuickBird image, the resolutions of multi-spectral with four bands and panchromatic image are 2.44m and 0.61m respectively. The process of image fusion is implemented mainly in the fuzzy tool of Matlab. Lastly, assessing the quality of resulting images and these methods of evaluation is based on visually and statistically. The findings that the fused image has remained the attributes of multi-spectral image and high resolution image with 0.61m instead of 2.44m. It is indicated that the fused image is finer than the original multi-spectral image. So the approach of this paper has presented could be a good method to process remote sensing image fusion.
机译:现在已经在遥感数据的过程中使用了图像融合技术。它可以集成来自多传感器数据的信息,以便补充单个传感器图像的短缺,​​然后更适合于人类视觉感知,计算机辅助对象检测和目标识别。目前,我们可以从其他研究人员的研究中获得许多图像融合方法,但这些图像融合方法具有一些缺点。本文呈现的图像融合的与模糊理论像素级的办法,在本文中所使用的数据的源是来自快鸟图像,多光谱具有四个带和全色图像的分辨率分别2.44米和0.61米。图像融合过程主要在Matlab的模糊工具中实现。最后,评估所得图像的质量和这些评估方法基于视觉和统计学。熔融图像仍然是0.61米而不是2.44M的多光谱图像和高分辨率图像的属性。表示融合图像比原始多光谱图像更精细。因此,本文的方法呈现可能是处理遥感图像融合的好方法。

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