Panoramic video coding-oriented quick global motion estimation method

Abstract

The invention discloses a panoramic video coding-oriented quick global motion estimation method. The method comprises two steps of: 1, using a brightness residual threshold value model, which is based on the combination of statistic characteristics and mean of threshold values, to approximately divide a local motion area and a global motion area, and obtaining an approximate set of a global motion estimation area; and 2, adopting the motion vector residual grading threshold value technology to gradually detail the set of global motion pixels in a minimum iterative process of the energy residual function and finally separating the complete global motion area so as to achieve an aim of quick motion estimation. The method has the advantages of taking both accuracy and robustness of the global motion estimation into consideration, greatly saving cost of calculating the motion estimation under the condition of ensuring the quality of the re-constructed image does not decline, but is improved a little bit, and having effects of low algorithm complexity and accurate estimation of motion parameters on the global motion estimation of the panoramic video sequence.

Description

technical field [0001] The invention relates to an image video coding compression technology, in particular to a fast global motion estimation method for panoramic video coding. Background technique [0002] 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 a fixed axis, and takes pictures of different orientations of the scene around the camera in the same time domain, and uses some "stitching" techniques for these pictures Seamless splicing, and then mapped into a cylindrical or spherical map according to the cylindrical or spherical mapping algorithm. Therefore, the resolution of the panoramic image is generally higher, and the motion details are richer. Moreover, since the panoramic video generally supports virtual camera motion reproduction in order to allow users to have a real scene experience, the interlacing...

AI Technical Summary

Problems solved by technology

However, since the proportion of the global motion area to the entire scene in different videos is different, this method can only obtain part of the global motion area, or the set of internal points will contain many outliers.

Some scholars have proposed an improved method: let the threshold T be the mean value of the residuals of all pixels (called the residual mean threshold method), but the residual mean method does not necessarily describe the global motion area and the local area well. The difference in the motion area, the experimental results also show that in some cases this method may make the interior point set converge to the local motion area

[0006] The above-mentioned inner region determination methods are difficult to balance the accuracy and robustness of parameter estimation, and often need to select an ideal threshold in advance for different video scenes, which has poor adaptability

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