Liu Xuan, Zhang Lijun, Kirby Mitchell, Becker Richard, Qi Shaohai, Zhao Feng
J Opt Soc Am A Opt Image Sci Vis. 2016 Apr 1;33(4):630-6. doi: 10.1364/JOSAA.33.000630.
In this study, we developed a signal processing method for fixed pattern noise removal in fiber-bundle-based endoscopic imaging. We physically acquired the fixed pattern of the fiber bundle and used it as a prior image in an l norm minimization (l-min) algorithm. We chose an iterative shrinkage thresholding algorithm for l norm minimization. In addition to fixed pattern noise removal, this method also improved image contrast while preserving spatial resolution. The effectiveness of this method was demonstrated on images obtained from a dark-field illuminated reflectance fiber-optic microscope (DRFM). The iterative l-min algorithm presented in this paper, in combination with the DRFM system that we previously developed, enables high-resolution, high-sensitivity, intrinsic-contrast, and in situ cellular imaging which has great potential in clinical diagnosis and biomedical research.
在本研究中，我们开发了一种用于基于纤维束的内窥镜成像中去除固定模式噪声的信号处理方法。我们通过物理方式获取了纤维束的固定模式，并将其用作l范数最小化（l-min）算法中的先验图像。我们选择了一种用于l范数最小化的迭代收缩阈值算法。除了去除固定模式噪声外，该方法还在保留空间分辨率的同时提高了图像对比度。该方法的有效性在从暗场照明反射光纤显微镜（DRFM）获得的图像上得到了证明。本文提出的迭代l-min算法，与我们之前开发的DRFM系统相结合，能够实现高分辨率、高灵敏度、固有对比度和原位细胞成像，在临床诊断和生物医学研究中具有巨大潜力。
