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SYSTEMS AND METHODS FOR MULTI-SPECTRAL IMAGE FUSION USING UNROLLED PROJECTED GRADIENT DESCENT AND CONVOLUTINOAL NEURAL NETWORK
SYSTEMS AND METHODS FOR MULTI-SPECTRAL IMAGE FUSION USING UNROLLED PROJECTED GRADIENT DESCENT AND CONVOLUTINOAL NEURAL NETWORK
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机译:使用展开投影梯度下降和卷积神经网络的多光谱图像融合系统和方法
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摘要
Systems, methods and apparatus for image processing for reconstructing a super resolution (SR) image from multispectral (MS) images. A processor to iteratively, fuse a MS image with an associated PAN image of the scene. Each iteration includes using a gradient descent (GD) approach with a learned forward operator, to generate an intermediate high-resolution multispectral (IHRMS) image with an increased spatial resolution and a smaller error to the DSRMS image compared to the stored MS image. Project the IHRMS image using a trained convolutional neural network (CNN) to obtain an estimated synthesized high-resolution multispectral (ESHRMS) image, for a first iteration. Use the ESHRMS image and the PAN image, as an input to the GD approach for following iterations. The updated IHRMS image is an input to another trained CNN for the following iterations. After predetermined number of iterations, output the fused high-spatial and high-spectral resolution MS image.
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