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Image Fusion in Compressed Sensing Based on Non-subsampled Contourlet Transform

机译:基于非下采样Contourlet变换的压缩感知图像融合

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A fusion method based on non-subsampled contourlet transform (NSCT) in compressed sensing was proposed. The method decomposes two or more original images using NSCT, and gets the sparse matrix by the NSCT coefficients sparse representation, and fuses the sparse matrices with the coefficients absolute value maximum scheme. The compressed sample can be received through randomly observed. The fused image is recovered from the reduced samples by solving the optimization. The simulations show that the proposed CS-based image fusion algorithm has the advantages of simple structure and easy implementation, and also can achieve a better fusion performance.
机译:提出了一种基于非下采样轮廓波变换(NSCT)的压缩感知融合方法。该方法使用NSCT分解两个或更多个原始图像,并通过NSCT系数的稀疏表示获得稀疏矩阵,并将稀疏矩阵与系数绝对值最大值方案融合。压缩样品可以通过随机观察接收。通过解决优化问题,从减少的样本中恢复融合图像。仿真结果表明,所提出的基于CS的图像融合算法具有结构简单,易于实现的优点,并且可以获得较好的融合性能。

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