Image mosaic splices several adjacent overlapped images into an integrated seamless picture which could be significant
in medical image processing. However, because of image acquisition, a mismatch could occur as a result of adjacent
image stitching data and cumulative errors. The current method which is effective in certain ways still has room for
improvement regarding processing speed and effectiveness, particularly in accuracy. This paper proposed a new image
mosaic revising algorithms based on the relativity of adjacent images location, expounding the principal of image mosaic
unit, the equations on splicing parameters and the simplified rules as well as achieving automatic calculation through
application of revised algorithm. By experiment, the 20 groups inaccurate pathological mosaic images were revised
rapidly and accurately with error controlled within a pixel. It is proved that the approach is effective in revising the error
matching in microscopic images mosaic.
Blood vessel images have strongly morphological characteristic as well as complicated backgrounds. However,
traditional boundary extraction algorithms rarely utilize the local uniform direction of the pixels in the vascular margin
and often incur discontinuities of edges due to background noises. In this paper a new vascular boundary extraction
algorithm based on direction filtering is presented, in which some algorithms, such as chaotic filtering, direction and
distance matrix, as well as edge tracing, are put forward. The experimental results indicate that the algorithm has
achieved better effects in noise depression and vascular extraction.