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Entropy dependent compressive sensing based image fusion

机译:基于熵的熵依赖性压缩感应图像融合

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摘要

An entropy dependent compressive sensing based image fusion is proposed which adaptively adjusts the number of compressive measurements depending on the amount of information (computed using entropy). Since the computational complexity is dependent on the number of compressive measurements, the proposed scheme is more efficient and accurate. Simulation results show the significance of the proposed scheme compared to existing compressive sensing based state of art scheme.
机译:提出了一种基于熵的基于压缩感测的图像融合,其根据信息量(使用熵计算)自适应地调整压缩测量的数量。由于计算复杂性取决于压缩测量的数量,所以该方案更有效和准确。仿真结果表明,与现有的基于压缩感测的艺术方案相比,该方案的重要性。

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