A Fast Digital Image Stabilization Method for Space Robot Vision System

Abstract

The invention discloses a fast digital image stabilization method suitable for a space robot vision system, and relates to a fast digital image stabilization technology, which consists of five parts: image preprocessing, local motion estimation, global motion estimation, motion filtering and motion compensation. . The present invention uses the ORB feature point extraction algorithm on the basis of image preprocessing to quickly and accurately perform feature point extraction and matching on front and rear frame images, and has advantages in time and precision. After the matching point pairs are obtained, the global motion vector can be accurately solved by using the Haus Herder transformation method and the generalized matrix method, which lays the foundation for subsequent motion filtering and compensation. Then the damping coefficient method can preserve the random jitter motion component and eliminate the normal scanning component. Finally, the position of each pixel of a single frame image is adjusted by the linear combination of global motion vectors between frames to obtain a stable video image sequence. The time complexity is low, and the prediction and compensation accuracy is high.

Description

technical field [0001] The invention belongs to the field of image processing and computer vision, and in particular relates to a fast digital image stabilization method suitable for a space robot vision system. Background technique [0002] Digital stabilization is a technique for correcting non-stationary video image sequences acquired by a camera system moving randomly. Its purpose is to eliminate the displacement of the same object on different frame image coordinates in the image sequence caused by redundant motion of the carrier, and then eliminate the blurring and jitter of the image sequence observed due to visual persistence. Compared with mechanical image stabilization and optical image stabilization, digital image stabilization has the characteristics of high precision, easy operation, strong flexibility, less hardware, and small size. In foreign countries, it has been widely used in various tasks such as photography, aerial reconnaissance, weapon system observat...

AI Technical Summary

Problems solved by technology

Among them, the gray-scale projection method has the characteristics of small amount of calculation and high precision, but it is not effective for image stabilization such as rotation, scaling, and large translational movements; the block matching method has high precision, but is affected by the search strategy and matching criteria. The image stabilization effect is uneven; the optical flow field method has aperture problems and occlusion problems, and its optical flow constraint equation is not strictly established, which requires a large amount of calculation and has large errors; the phase method has a large amount of calculation and is difficult to guarantee real-time performance; the feature matching method Being able to quickly and effectively stabilize image sequences that shake in any form is the main direction for the development of digital image stabilization in the future

However, it has two problems: one is how to extract image features stably, accurately and quickly; the other is how to quickly and accurately match image features

The disadvantages of this scheme are that the processing process is cumbersome, the amount of calculation is large, the range of jitter that can be processed is small, and the image quality is affected during the image conversion process.

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