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Topological Derivative Improved Partial Differential Equation for Infrared Spectral Data Denoising

机译:红外光谱数据去噪的拓扑衍生改进的部分微分方程

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To reduce the influence of noise in infrared spectral signal measurement, a topological derivative improved partial differential equation method for infrared spectral data denoising is proposed. As an indicator function, topological derivative through a minimization process to find the best position to introduce disturbance, where are spectral edge points, then select the most excellent diffusion coefficient, so the cost of the minimum functional value. Based on the idea of topological optimization, it makes the lowest topological derivative to be optimum one. Then the diffusion is applied by using partial differential equation. Several simulated infrared spectral sequences are utilized to verify the performance of the proposed method. The experiment results show that our method is better in denoising.
机译:为了减少红外光谱信号测量中噪声的影响,提出了一种用于红外光谱数据去噪的拓扑衍生改进的部分微分方程方法。作为指示灯函数,通过最小化过程拓扑导数来找到引入干扰的最佳位置,在其中是光谱边缘点,然后选择最优异的扩散系数,因此最小功能值的成本。基于拓扑优化的思想,它使最低的拓扑衍生物成为最佳的衍生物。然后使用偏微分方程施加扩散。有几种模拟的红外光谱序列用于验证所提出的方法的性能。实验结果表明,我们的方法在去噪方面更好。

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