A video frame rate up-conversion method and system based on motion region segmentation

Abstract

The invention discloses a video frame rate up-conversion method and system based on motion region segmentation. The method comprises the steps of extracting feature points of video images; matching the feature points between the images and obtaining motion vectors of the feature points; clustering the motion vectors of the feature points and extracting motion region information; propagating the motion information of motion regions to each other pixel in the images starting from the feature points, thereby obtaining per-pixel motion region segmentation results and initial per-pixel motion vector fields; carrying out smooth filtering on the motion vector fields according to the per-pixel motion region segmentation results, thereby obtaining optimized motion vector fields; and carrying out compensation interpolation according to the motion vector fields, thereby obtaining interpolation frame images and finishing up-conversion of a frame rate. According to the method and the system, the motion region information in a video can be obtained accurately, motion estimation and motion vector filtering can be assisted effectively, the up-conversion of the video frame rate is finished, and the video watching experience is improved.

Description

technical field [0001] The invention belongs to the field of video frame rate up-conversion, and in particular relates to a video frame rate up-conversion method and system based on motion region segmentation. Background technique [0002] Video frame rate up-conversion is a technology for up-converting low frame rate video to high frame rate video to improve video viewing experience. It estimates an intermediate frame between the original frames of the low frame rate video through digital signal processing to achieve a smoother transition of object motion. [0003] Based on this purpose, most frame rate up-conversion algorithms are divided into two steps: first, the information about the motion of the object in the video is estimated by a certain technology, and then the position and position of the object in the middle frame are estimated by using this information. Pixel values. Generally, the former is called motion estimation, and the latter is called motion-compensate...

AI Technical Summary

Problems solved by technology

[0007] However, the above-mentioned invention belongs to a block-based motion estimation method, which has poor performance in obtaining real motion vectors. Although the median filtering method based on time domain and space domain is used to filter out wrong motion vectors, at the edge of moving objects, The optimality of the vector field is still not guaranteed

Therefore, the video generated by this invention will leave more defects near moving objects

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