Rapid and steady image splicing method based on medical microscopic imaging

Abstract

The invention discloses a rapid and steady image splicing method based on medical microscopic imaging, and belongs to the field of image processing. To achieve high speed, high-precision microscopic image splicing, the rapid and steady image splicing method selects an ORB algorithm to extract image features to prove that through processing, the same precision can be achieved through the method andalgorithms such as SIFT and SURF, and the calculated amount can be reduced on feature extraction. Besides, in order to eliminate the mixed gap to generate a seamless image, the rapid and steady imagesplicing method adopts a gradual-in gradual-out weighted average strategy, and in the final fusion stage, the rapid and steady image splicing method adopts the image indexing operation, so that multiple times of copying and moving of pixels are avoided to the maximum extent, and the time is further shortened. In addition, for the rapid and steady image splicing method, the whole algorithm processis accelerated by using a GPU, and the algorithm processing time is reduced to the minimum. Through calculation, for the rapid and steady image splicing method, accurate seamless splicing can be completed within about one second by using a 3 * 3 image with the resolution of 1360 * 1024.

Description

technical field [0001] The present invention is a fast and robust image mosaic technology based on medical microscopic imaging, specifically a method that can quickly and automatically realize the accurate and accurate stitching of a large number of high-resolution microscopic pictures such as 3×3, 5×5 or 10×10. A seamless approach. Background technique [0002] The patent application No. 201710879986.8 discloses an image acquisition and stitching method for a large-scale microscopic imaging area. The method matches the feature points, and the matching results are calculated by the RANSAC algorithm to calculate the affine transformation matrix of each matching point; after obtaining the transformation matrix, use the matrix to transform the two images into the same coordinate system; use the grayscale of the two images According to the matching points in the overlapping area, the overlapping area of ​​the two images is covered to complete the splicing." The method stitches ...

AI Technical Summary

Problems solved by technology

[0003] In order to overcome the problem of slow speed and low efficiency of manual observation of samples by doctors or researchers when it is necessary to observe microscopic images of multiple fields of view to make a diagnosis, the present invention proposes a solution for this, automatically combining high-resolution images from multiple fields of view. The pictures are automatically stitched and the mixed seam is eliminated to produce a seamless image, which achieves the purpose of fast and efficient, and the fast stitching also lays a solid foundation for improving the recognition rate of microscopic images

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