Multi-source video stitching method and device

Abstract

The invention discloses a multi-source video stitching method and device, and the method comprises the steps: decomposing a multi-source video into a plurality of frame images, stitching the corresponding frame images respectively to obtain an observer imaging surface, and generating an observer video according to the observer imaging surface; according to the method, dividing the video into multiple frames of images, splicing each frame of image, and in the splicing process, converting the coordinates of the pixel points in the imaging surface of the observer through the observation angle, then calculating the intersection points of the pixel points and the imaging surface of each camera through the pixel points, and generating the pixel values of the pixel points in the imaging surface of the observer through the pixel values of the intersection points, so that the image splicing speed in a video source can be improved, and the video splicing efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of video processing, and in particular relates to a multi-source video splicing method and device. Background technique [0002] The Distributed Aperture Sensor System (Distributed Aperture Sensor, DAS) originated from a project of researching the Distributed Aperture Infrared Sensor System (DAIRS) for fighter jets, in which the problem of multi-source image stitching based on the DAS system was mentioned for the first time. Later, with the development of information technology, this technology was gradually extended to the civilian field. At present, the broad sense of DAS system refers to the photoelectric sensor system distributed on transportation equipment such as aircraft, ships and automobiles. [0003] Video stitching technology is to convert video into images. Image stitching is a relatively comprehensive technology in the field of image processing. The purpose is to combine two or more partially ov...

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Problems solved by technology

[0004] However, when the environment in the video is relatively complex, such as in the forest area, the trees and leaves are particularly dense, resulting in very dense feature points and high similarity. When the conventional image stitching method is used for image stitching, it will take a lot of time. It is difficult to achieve real-time output of video, resulting in low efficiency of video splicing

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