Combining super-resolution localization microscopy with pathology creates new opportunities for biomedical researches. This combination requires a suitable image mosaic method for generating a panoramic image from many overlapping super-resolution images. However, current image mosaic methods are not suitable for this purpose. Here we proposed a computational framework and developed an image mosaic method called NanoStitcher. We generated ground truth datasets and defined criteria to evaluate this computational framework. We used both simulated and experimental datasets to prove that NanoStitcher exhibits better performance than two representative image mosaic methods. This study is helpful for the mature of super-resolution digital pathology.

The rapid development of unmanned aerial vehicles (UAVs), miniature hyperspectral imagers, and relevant instruments has facilitated the transition of UAV-borne hyperspectral imaging systems from concept to reality. Given the merits and demerits of existing similar UAV hyperspectral systems, we presented a lightweight, integrated solution for hyperspectral imaging systems including a data acquisition and processing unit. A pushbroom hyperspectral imager was selected owing to its superior radiometric performance. The imager was combined with a stabilizing gimbal and global-positioning system combined with an inertial measurement unit (GPS/IMU) system to form the image acquisition system. The postprocessing software included the radiance transform, surface reflectance computation, geometric referencing, and mosaic functions. The geometric distortion of the image was further significantly decreased by a postgeometric referencing software unit; this used an improved method suitable for UAV pushbroom images and showed more robust performance when compared with current methods. Two typical experiments, one of which included the case in which the stabilizing gimbal failed to function, demonstrated the stable performance of the acquisition system and data processing system. The result shows that the relative georectification accuracy of images between the adjacent flight lines was on the order of 0.7–1.5 m and 2.7–13.1 m for cases with spatial resolutions of 5.5 cm and 32.4 cm, respectively.