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Optimization Details-Based Injection Model for Remote Sensing Image Fusion

机译:基于优化细节的遥感图像融合注入模型

摘要

#$%^&*AU2020100179A420200319.pdf#####Abstract: With the rapid development of satellite sensors, remote sensing images have been widely applied. However, due to the limitations of sensor technology and other factors, the existing remote sensing sensors cannot get high spatial resolution (HR) multispectral (MS) images at the same time. This present patent investigates a method to reconstruct HRMS image that is combine with HR panchromatic (PAN) image and low spatial resolution (LR) MS image. First, the fusion high-frequency information of PAN and MS image is obtained by a low-rank fuzzy fusion (LRFF) model to fuse the high-frequency details of PAN and MS images. Then, the high-frequency information after fusion is compensated by detail compensation model as injection detail. Finally, the injection detail is injected into the upsampled LRMS image to achieve a fused image.
机译:#$%^&* AU2020100179A420200319.pdf #####抽象:随着卫星传感器的快速发展,遥感图像已得到广泛应用。但是,由于传感器技术的局限性和其他因素,现有的遥控器感应传感器无法同时获得高空间分辨率(HR)多光谱(MS)图像时间。本专利研究了一种重建HRMS图像的方法,该方法与HR全色(PAN)图像和低空间分辨率(LR)MS图像。一,融合通过低秩模糊融合(LRFF)获得PAN和MS图像的高频信息模型以融合PAN和MS图像的高频细节。然后,高频融合后的信息由细节补偿模型作为注入细节进行补偿。最后,注入细节被注入到上采样的LRMS图像中以获得融合图像。

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