IEEE Trans Med Imaging. 2022 Dec;41(12):3862-3872. doi: 10.1109/TMI.2022.3198946. Epub 2022 Dec 2.
A flat-field correction method is proposed for multiple measured hyperspectral microscopy imaging in this paper. As the most crucial preprocessing process in quantitative microscopic analysis, flat-field correction solves the uneven illumination caused by vignetting in microscopic images, and guarantees the precision of spatial and spectral information in hyperspectral microscopic imaging. In order to carry out flat-field correction and extract uneven illumination among groups of hyperspectral microscopic data containing hundreds of bands simultaneously, two properties of vignetting have been exploited: i) low-rank property is reflected by little information contained in vignetting; ii) local smoothness can be observed as a gradual change in brightness of vignetting, which is typically equivalent to the sparseness in spatial frequency domain. Combining the two properties above, a novel Low Rank Smooth Flat-field Correction (LRSFC) model modified from common orthogonal basis extraction is proposed, while an optimization is solved based on alternating direction multiplier method (ADMM), obtaining a unique flat-field term with low-rank and smooth properties. Qualitative and quantitative experimental assessments indicate that LRSFC does not add extra cell texture to the extracted flat-field term, whose performance appears prior to other state-of-the-art flat-field correction methods.
本文提出了一种用于多次测量的高光谱显微镜成像的平场校正方法。作为定量微观分析中最关键的预处理过程，平场校正解决了显微镜图像中由于渐晕引起的不均匀照明问题，保证了高光谱显微镜成像中空间和光谱信息的精度。为了对包含数百个波段的高光谱显微镜数据进行平场校正并同时提取组内的不均匀照明，利用渐晕的两个特性：i）低秩特性反映了渐晕中包含的信息量较少；ii）局部平滑度可以观察到渐晕中亮度的逐渐变化，这通常相当于空间频率域中的稀疏性。结合这两个特性，提出了一种从常见正交基提取方法修改而来的新的低秩平滑平场校正（LRSFC）模型，同时基于交替方向乘子法（ADMM）进行优化求解，得到了具有低秩和平滑特性的唯一平场项。定性和定量实验评估表明，LRSFC 不会向提取的平场项中添加额外的细胞纹理，其性能优于其他最先进的平场校正方法。
