Self-adaptively selecting global motion estimation method for panoramic video coding

Abstract

The invention discloses self-adaptively selecting global motion estimation method for panoramic video coding, which comprises the following steps that: (1) an image is divided into a plurality of sub-image blocks, (2) zero vector block is decided, (3) multi-resolution motion is estimated, (4) translational motion model motion parameter is estimated, (5) six-parameter motion model motion parameter is estimated, (6) twelve-parameter motion model motion parameter is estimated, and (7) RDO optimizes an estimation model of self adaptively choosing global motion. The advantage is that the estimation model of self adaptively choosing global motion optimized by the RDO can well describe the camera motion flow characteristic of the current frame well so that the motion estimation is more accurate and the coding performance is higher. At the same time, aiming at the characteristics of the rich detail and the high resolution ratio of panoramic video motion, the invention takes the Lagrange parameter Lambada=0.85x2QP / 3+2QP / 6 and further obtains a good balance between compression code rate and image distortion degree.

Description

technical field [0001] The invention relates to an image video coding compression technology, in particular to a motion estimation method for panoramic video coding. Background technique [0002] Video based on image rendering is a kind of omnidirectional video. Omnidirectional video is also called immersive video. The purpose of omnidirectional video is to provide users with a virtual reality experience, so that users can observe the surrounding scenes stitched together with photo images. Its basic idea is to use images, rather than geometric figures, as basic units to form scenes, and at the same time support virtual camera movements, such as global movements such as rotation and scaling. A typical representative of omnidirectional video is panoramic video. [0003] Panoramic video is widely used in sports programs, 3D movies, multi-party video conferencing and other applications. A panoramic image is a six-sided or eight-sided fisheye camera that rotates or zooms around...

AI Technical Summary

Problems solved by technology

However, multi-parameter motion models must pay more computational complexity

Since the global motion estimation is based on the principle of solving the minimum value of the error function, under the existing algorithm framework, such as the Gauss-Newton iterative method and the Levenberg-Marquardt iterative method, the more motion parameters to be estimated, the more complex the iterative algorithm will be. high (multiplied)

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