Image stitching for pathological slice splices several adjacent images into an integrated seamless picture which is significant in remote medicine, especially remote diagnosis. However, because of limitations of image acquisition method, some mismatch could occur. This paper proposed a new image mosaic revising algorithms based on the relativity of adjacent images. After experimental verification, the 20 groups inaccurate pathological mosaic images were revised rapidly and accurately with error controlled within a pixel. It is proved that the algorithm is effective in revising the error matching in pathological images mosaic.

Microscopic image mosaic stitches several adjacent images into an integrated seamless picture, and is of significant practical value to remote medicine applications, especially in remote diagnosis. However, due to limitation in image acquisition method, a mismatch could occur as a result of variance in adjacent image stitching data and accumulation of errors. The current image stitching method still has room for improvement regarding processing speed and effectiveness, particularly in precision. In this paper, we proposed a new image mosaic revising algorithms based on the relativity of adjacent images and expounding the principal and equations on image mosaic error revising, as well as achieving automatic intelligent calculation with the revised algorithm. Through experiment, inaccurate pathological mosaic images from 20 groups were revised rapidly and accurately with error controlled within one pixel. It was proved that the approach is effective in revising the error matching in microscopic images mosaic. Moreover, it is easy to operate and effective for more accurate image stitching.