Video deblurring method and device, equipment and storage medium

Abstract

The invention provides a video deblurring method and device, equipment and a storage medium, which can be applied to various scenes such as cloud technology, artificial intelligence, smart traffic, auxiliary driving and videos. The method comprises the following steps: obtaining a current image in a video and N adjacent images of the current image; extracting first feature information of the current image under M scales and second feature information of each adjacent image in the N adjacent images under the M scales; aiming at each adjacent image in the N adjacent images, aligning the second feature information of the adjacent images under the M scales with the first feature information under the M scales; and obtaining a deblurred current image according to the second feature information of each adjacent image in the N adjacent images after alignment under the M scales. According to the invention, in a feature domain, the first feature information of the current image is aligned with the second feature information of the adjacent images, so that the video deblurring effect is improved.

Description

technical field [0001] The embodiments of the present application relate to the technical field of image processing, and in particular, to a video deblurring method, device, device, and storage medium. Background technique [0002] In the process of video capture, due to the shaking of the camera equipment, the rapid movement of objects and other reasons, the video will inevitably be blurred. In order to improve the display effect of the video or improve the accuracy of video-based task analysis, it is necessary to deblur the blurred video, that is, restore a clear video from the blurred video. [0003] Current video deblurring methods use an optical flow model to align the current image with its neighbors in the image domain. Based on the aligned current image and adjacent images, the attention mechanism is used to calculate the regional similarity. The features of the similar area are fused to the current area to obtain the fused features of the current image, and finall...

AI Technical Summary

Problems solved by technology

[0004] However, when using the optical flow model to align the current image with adjacent images in the image domain, once the scene changes quickly and the distance is far away, the estimation of the optical flow field will be wrong, which will cause defects in the alignment results and lead to the current image’s inaccuracy. Poor deblurring effect

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