Image splicing method and equipment

Abstract

The invention discloses an image splicing method and image splicing equipment which are used for splicing an image rapidly and do not reduce the quality of the spliced image. The method comprises the following steps of: determining a quilt between a first image and a second image; dividing pixels of the first image and the second image into a foreground pixel and a background pixel; splicing the foreground pixel of the first image and the second image based on the quilt; and deforming the background pixel and enabling the background pixel to be fused with the spliced foreground pixel. The method has the characteristics of simple algorithm and high speed. Layered splicing is adopted, and background deformation adapts to the foreground pixel splicing, therefore the inconsistency of vision is eliminated and the quality of image splicing is high.

Description

technical field [0001] The invention relates to an image splicing technology, in particular to an image splicing method and equipment. Background technique [0002] The technology of seamlessly stitching images taken at different angles or positions to form a high-resolution panorama is called image stitching. Image stitching technology research is an important field of computer vision research. This technology has a wide range of uses, such as the synthesis of satellite images or aerial images, the establishment of panoramic virtual scenes, photo editing, etc. With the advancement of technology in this field, image stitching has entered people's daily life. For example, in digital cameras, panorama composition has become a function of digital cameras. [0003] Video stitching is a special image stitching technology. The purpose of video stitching is to synthesize video images from different video sources to obtain a high-resolution wide-angle video. With the rapid devel...

AI Technical Summary

Problems solved by technology

However, this method is sensitive to parallax, and the stitched images are prone to ghosting effects

The image stitching algorithm using optical flow technology can effectively deal with the ghost effect, but the optical flow calculation is very time-consuming and unstable

Stitched image quality is relatively low

Layering optical flow calculations can improve the accuracy and stability of optical flow calculations, but image segmentation is also a pathological problem

Therefore, imprecise optical flow calculations will cause new visual discontinuities, such as unclear edges, ghost images, etc.

[0018] Considering the amount of calculation, the video stitching algorithm is often derived from the image stitching algorithm based on the parameter model, so it is also prone to ghost effects and obvious stitching

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