High resolution and large field of view imaging using a stitching procedure coupled with distortion corrections

A numerical approach was implemented to precisely stitch together images from the same projector/camera that form a mosaic by regularly moving either the projector/camera or the scene/sample. Such an imaging approach is used, for example, in automated microscopy. The presence of optical distortions can lead to detrimental blurring artifacts in the overlaps. The present development identifies and corrects non-affine distortion functions using the gray-level conservation equation on reduced overlapping regions of adjacent images with sub-pixel accuracy. The present numerical development was first tested on synthetic images with known distortions to confirm that the algorithm is capable of detecting only non-affine distortions. Then, Digital Image Correlation (DIC) was applied to a pair of large laser scanning confocal microscope mosaics (121 images of 1024 × 1024 pixel², i.e., more than 100 MPixel) created using the proposed non-rigid stitching. The method aims to improve the quality of blended images after stitching using the sample pattern in the overlapped regions. This new numerical development significantly minimizes kinematic field artifacts due to lens distortion in overlapped regions.