Region-matching-based fast electronic image stabilization method

Abstract

The invention relates to a region-matching-based fast electronic image stabilization method, which specifically comprises the following steps: (1) reading video image frames, and selecting a first frame of an image as a reference frame; (2) sequentially performing region matching on current frames and the reference frame to obtain matching scores by adopting an MSER (maximally stable extremal region) algorithm, performing wavelet transformation, sequencing the obtained matching scores from high to low scores, and selecting regions corresponding to the first n matching scores; (3) performing region labeling on the regions corresponding to the selected first n matching scores, performing FAST characteristic point detection on the labeled regions, and extracting characteristic points; (4) performing characteristic point matching, and estimating a motion parameter; (5) performing reverse motion compensation on the image. According to the method, an image sequence is stabilized by virtue of an image stabilization algorithm, so that the method has the advantages of fastness, high accuracy, low power consumption and the like.

Description

technical field [0001] The invention relates to a fast electronic image stabilization method based on area matching, which belongs to the technical field of digital image processing. Background technique [0002] In recent years, with the vigorous development of computers and related technologies, the technology has been updated in real time, and many methods that originally required related mechanical equipment and mechanical technology can be directly replaced by low-cost and high-efficiency electronic software and hardware. The development of image stabilization technology has gone through three stages from mechanical to optical, and then to the current electronic image stabilization technology. Electronic image stabilization technology uses digital image processing technology to estimate the motion of a series of images in the video, and then perform reverse motion Compensation is a technique to remove abnormal shifts in an image such as jitter, rotation, etc. [0003] ...

AI Technical Summary

Problems solved by technology

[0010] The third is that when detecting the motion vector of the camera, there will be background noise, such as the movement or movement of small objects in the foreground, the shaking of branches and leaves in the background, the movement of the target itself, and the entry of foreign objects into the field of view, etc. will affect the motion of the image acquisition device. Extraction of vectors adversely affects

[0012] In the traditional algorithm, especially the movement of the foreground will cause the output image of the electronic image stabilization to become smaller and smaller, so that the video shape will eventually be distorted and cannot be output normally.

Traditional algorithms cannot guarantee the unity of real-time and performance

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