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A fast, low complexity image fusion algorithm based on multiscale transforms

机译:基于多尺度变换的快速,低复杂度图像融合算法

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In this paper, a novel image fusion algorithm based primarily on an improved multi-scale coefficient decomposition framework is proposed. The proposed framework uses a combination of non-subsampled contourlet and wavelet transforms for the initial multi-scale decompositions. The decomposed multiscale coefficients are then fused twice using various local activity measures. Experimental results show that the proposed approach performs better or in par with the existing state-of-the art image fusion algorithms in terms of quantitative and qualitative results. In addition, the proposed image fusion algorithm can produce high quality fused images even with a computationally inexpensive two-scale decomposition.
机译:提出了一种主要基于改进的多尺度系数分解框架的图像融合算法。所提出的框架使用非下采样轮廓波和小波变换的组合进行初始的多尺度分解。然后使用各种局部活动度量将分解后的多尺度系数融合两次。实验结果表明,所提出的方法在定量和定性结果方面表现更好,或与现有的最新图像融合算法相媲美。另外,所提出的图像融合算法即使在计算上便宜的两尺度分解中也可以产生高质量的融合图像。

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