Video frame rate up-conversion method and system for improving motion fluency intelligently

Abstract

The present invention discloses a video frame rate up-conversion method and system for improving motion fluency intelligently. The method comprises a first step of pre-analyzing two frames of continuous original video image; a second step of performing motion estimation on the two frames of image; a third step of calculating a new interpolated frame between the two frames of original image according to estimated motion information; a fourth step of performing post processing like hole filling, block-effect filling, image quality evaluation on the interpolated frame image; and a fifth step of according to information of the four previous steps, determining whether to replace the interpolated frame with a repeated frame. On the basis of the method, the present invention provides a video frame rate up-conversion system for improving motion fluency intelligently. Due to the frame rate up-conversion, stream of each processing module is controlled, so that high reuse and high parallelism of the information of all modules are realized. Through adoption of the method and system, high quality video frame rate improvement is realized at a source end, and the video motion fluency is improved intelligently.

Description

technical field [0001] The invention belongs to the field of video frame rate up-conversion, and in particular relates to a method and system for intelligently improving motion fluency at the source end, adopting various methods for intelligent fusion, selection or judgment of each process of frame rate up-conversion. Background technique [0002] Video frame rate up-conversion is a basic problem in the field of video image processing. It is to insert a video with a low frame rate into a video with a high frame rate by inserting an intermediate frame between the original video frames. The intermediate frame is also called interpolation. Frame, where the frame rate refers to the number of images refreshed per second. This method can improve the image jitter, stuttering, discontinuous motion of objects, and motion blur caused by low frame rate video viewing. [0003] With the development of the Internet and mobile Internet, a large number of videos are watched through network...

AI Technical Summary

Problems solved by technology

Moreover, they also lack the means of post-processing and quality judgment of interpolation images, so that they do not have a good ability to monitor the interpolation results.

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