Image processing method and device

Abstract

The invention provides an image processing method and an image processing device. The method comprises the following steps of: performing motion estimation on a first frame of image and a second frame of image to obtain motion vectors of the first and second frames of images; motioning the first frame of image by a part of distance of the motion vector along a motion track indicated by the motion vector to obtain an irregular motion vector field of an interpolated frame of image between the first and second frames of images; re-sampling the irregular motion vector field to obtain a regular motion vector field of the interpolated frame of image; and performing motion compensation on the regular motion vector field to obtain the interpolated frame of image. By the scheme, computational complexity is reduced, and simultaneously the accuracy of the output motion vector field is improved.

Description

technical field [0001] The present invention relates to data service processing, in particular to an image processing method and device. Background technique [0002] The frame rate up-conversion algorithm is mainly used for conversion between different frame rate video scanning formats, and can generate frames in an intermediate state in two or more frames of video images, such as figure 1 As shown, the video frame image 11 is at position A, the video frame image 13 is at position B, and the video frame image 12 is the frame in the intermediate state between the video frame images 11 and 13 . [0003] For example, in the field of low-bit-rate video communication, due to the limited transmission bandwidth, the video frame rate is usually low. By increasing the frame rate to 30fps, it can eliminate the incoherence and jumping when the screen is displayed, ensuring more Smooth dynamic effects. [0004] At present, there are two main categories of frame rate up-conversion alg...

AI Technical Summary

Problems solved by technology

If the traditional motion estimation based on the block matching algorithm is directly applied to the MC-FRUC algorithm, the images of the interpolated frames will have overlapping or empty problems, such as figure 2 As shown, the video frame image 21 is divided into several video image blocks, since the motion direction of each video image block may be arbitrary, the video image blocks in the video frame image 22 obtained by motion estimation overlap 221 or holes 222 ; Moreover, due to the flaws in the block processing itself, the continuity of the motion vector is poor, resulting in obvious block artifacts at the edge of the block in the interpolated frame

Traditional block motion estimation is only suitable for ordinary translational motions, not for complex motions such as rotation, scaling, and deformation

[0009] Therefore, in the process of implementing the present invention, the inventor found that in the existing image processing technology, especially the technology for generating interpolated frames, the motion estimation complexity is high, and the generated motion vector is difficult to accurately express the real motion; block-based motion compensation Holes and overlapping issues; blockiness and blurred images degrade the perceived quality of the video

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