Legesse F B, Chernavskaia O, Heuke S, Bocklitz T, Meyer T, Popp J, Heintzmann R
Leibniz Institute of Photonic Technology (IPHT) Jena e.V, Jena, Germany.
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg, Jena, Germany.
J Microsc. 2015 Jun;258(3):223-32. doi: 10.1111/jmi.12236. Epub 2015 Mar 18.
For diagnostic purposes, optical imaging techniques need to obtain high-resolution images of extended biological specimens in reasonable time. The field of view of an objective lens, however, is often smaller than the sample size. To image the whole sample, laser scanning microscopes acquire tile scans that are stitched into larger mosaics. The appearance of such image mosaics is affected by visible edge artefacts that arise from various optical aberrations which manifest in grey level jumps across tile boundaries. In this contribution, a technique for stitching tiles into a seamless mosaic is presented. The stitching algorithm operates by equilibrating neighbouring edges and forcing the brightness at corners to a common value. The corrected image mosaics appear to be free from stitching artefacts and are, therefore, suited for further image analysis procedures. The contribution presents a novel method to seamlessly stitch tiles captured by a laser scanning microscope into a large mosaic. The motivation for the work is the failure of currently existing methods for stitching nonlinear, multimodal images captured by our microscopic setups. Our method eliminates the visible edge artefacts that appear between neighbouring tiles by taking into account the overall illumination differences among tiles in such mosaics. The algorithm first corrects the nonuniform brightness that exists within each of the tiles. It then compensates for grey level differences across tile boundaries by equilibrating neighbouring edges and forcing the brightness at the corners to a common value. After these artefacts have been removed further image analysis procedures can be applied on the microscopic images. Even though the solution presented here is tailored for the aforementioned specific case, it could be easily adapted to other contexts where image tiles are assembled into mosaics such as in astronomical or satellite photos.
出于诊断目的,光学成像技术需要在合理的时间内获取扩展生物样本的高分辨率图像。然而,物镜的视野通常小于样本大小。为了对整个样本进行成像,激光扫描显微镜会采集拼接成更大拼接图的平铺扫描图像。这种图像拼接图的外观会受到可见边缘伪影的影响,这些伪影由各种光学像差引起,表现为跨平铺边界的灰度级跳跃。在本论文中,提出了一种将平铺图像拼接成无缝拼接图的技术。拼接算法通过平衡相邻边缘并将角点处的亮度强制为一个共同值来运行。校正后的图像拼接图似乎没有拼接伪影,因此适用于进一步的图像分析程序。本论文提出了一种将激光扫描显微镜捕获的平铺图像无缝拼接成大拼接图的新方法。开展这项工作的动机是现有的拼接我们显微镜设置所捕获的非线性、多模态图像的方法存在缺陷。我们的方法通过考虑此类拼接图中各平铺之间的整体光照差异,消除了相邻平铺之间出现的可见边缘伪影。该算法首先校正每个平铺内存在的不均匀亮度。然后,它通过平衡相邻边缘并将角点处的亮度强制为一个共同值来补偿跨平铺边界的灰度级差异。在去除这些伪影之后,可以对显微图像应用进一步的图像分析程序。尽管这里提出的解决方案是针对上述特定情况量身定制的,但它可以很容易地适用于其他将图像平铺组装成拼接图的情况,例如天文或卫星照片。