Department of Biomathematics, Institute of Physiology, Academy of Sciences of the Czech Republic, v.v.i., Vídeňská 1083, 14220 Prague 4, Czech Republic.
Microsc Res Tech. 2011 Sep;74(9):831-8. doi: 10.1002/jemt.20965. Epub 2010 Dec 3.
In images acquired by confocal laser scanning microscopy (CLSM), regions corresponding to the same concentration of fluorophores in the specimen should be mapped to the same grayscale levels. However, in practice, due to multiple distortion effects, CLSM images of even homogeneous specimen regions suffer from irregular brightness variations, e.g., darkening of image edges and lightening of the center. The effects are yet more pronounced in images of real biological specimens. A spatially varying grayscale map complicates image postprocessing, e.g., in alignment of overlapping regions of two images and in 3D reconstructions, since measures of similarity usually assume a spatially independent grayscale map. We present a fast correction method based on estimating a spatially variable illumination gain, and multiplying acquired CLSM images by the inverse of the estimated gain. The method does not require any special calibration of reference images since the gain estimate is extracted from the CLSM image being corrected itself. The proposed approach exploits two types of morphological filters: the median filter and the upper Lipschitz cover. The presented correction method, tested on images of both artificial (homogeneous fluorescent layer) and real biological specimens, namely sections of a rat embryo and a rat brain, proved to be very fast and yielded a significant visual improvement.
在共聚焦激光扫描显微镜 (CLSM) 获取的图像中,标本中相同荧光染料浓度的区域应映射到相同的灰度级别。然而,在实际中,由于多种失真效应的影响,即使是均匀的标本区域的 CLSM 图像也会出现不规则的亮度变化,例如图像边缘变暗和中心变亮。在真实生物标本的图像中,这些影响更为明显。空间变化的灰度图会使图像后处理变得复杂,例如在两个图像的重叠区域的对齐和 3D 重建中,因为相似性度量通常假设空间独立的灰度图。我们提出了一种基于估计空间变化光照增益的快速校正方法,并将获取的 CLSM 图像乘以估计增益的倒数。该方法不需要任何特殊的参考图像校准,因为增益估计是从要校正的 CLSM 图像本身中提取的。所提出的方法利用了两种形态滤波器:中值滤波器和上 Lipschitz 覆盖。所提出的校正方法在人工(均匀荧光层)和真实生物标本的图像(即大鼠胚胎和大鼠大脑的切片)上进行了测试,证明非常快速,并产生了显著的视觉改善。