NanoSIMS images are usually affected by random noises because of various types of sources, which degrade the quality of ion images and increase the uncertainty of the geochemical interpretations. Here, we applied the weighted nuclear norm minimization (WNNM) method to reduce the random noise in the NanoSIMS image. The low‐rank property of the image is fully considered to suppress random noise while retaining reliable details of weak signals. Numerical experiments on four different kinds of NanoSIMS ion images show that the denoising ability of the WNNM method is superior to that of the median filter, no matter the size of the filtering windows used (eg, 3 × 3, 5 × 5, and 7 × 7). The WNNM method can reduce random noise while preserving the most critical details in the original NanoSIMS observations, which can significantly enhance reliability when distinguishing critical boundaries and structures.

中文翻译：

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通过使用低秩方法减少随机噪声来增强NanoSIMS图像

由于各种类型的源，NanoSIMS图像通常会受到随机噪声的影响，这会降低离子图像的质量并增加地球化学解释的不确定性。在这里，我们应用加权核规范最小化（WNNM）方法来减少NanoSIMS图像中的随机噪声。充分考虑了图像的低秩特性，可以抑制随机噪声，同时保留微弱信号的可靠细节。在四种不同的NanoSIMS离子图像上进行的数值实验表明，无论使用的过滤窗口大小如何（例如3 × 3、5 × 5和7），WNNM方法的去噪能力均优于中值滤波器×7）。WNNM方法可以减少随机噪声，同时保留原始NanoSIMS观测结果中最关键的细节，从而在区分关键边界和结构时可以显着提高可靠性。