Abstract In recent years, terahertz (THz) imaging technology has attracted much attention in the detection of the integrated circuit (IC). However, limited by the hardware of the imaging system, THz images often contain a significant amount of noise, which impairs the quality of the image details. The THz image is also degraded due to the long wavelength. In this study, we propose a novel method for THz image restoration. We first apply a wavelet denoising technique to process the THz time-frequency signal. The point spread function (PSF) is then mathematically modeled to restore the details of the IC image, as the degradation of the THz image can be regarded as the convolution process of the object equation and PSF. Finally, we compare the performance between the restored THz images before and after wavelet denoising. The results demonstrate that the restored image after denoising performs better in peak signal-to-noise ratio and visual improvements, proving the practicability and precision of our proposed method.

中文翻译：

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基于小波去噪技术和点扩散函数模型的集成电路太赫兹图像复原

摘要 近年来，太赫兹（THz）成像技术在集成电路（IC）检测中备受关注。然而，受成像系统硬件的限制，太赫兹图像往往含有大量噪声，影响图像细节的质量。由于长波长，太赫兹图像也会退化。在这项研究中，我们提出了一种新的太赫兹图像恢复方法。我们首先应用小波去噪技术来处理太赫兹时频信号。然后对点扩散函数 (PSF) 进行数学建模以恢复 IC 图像的细节，因为太赫兹图像的退化可以看作是目标方程和 PSF 的卷积过程。最后，我们比较了小波去噪前后恢复的太赫兹图像的性能。