Fast Algorithm for Affine Motion Estimation Based on Statistical Analysis
To reduce the computational complexity of the new generation video coding standard-versatile video coding(VVC),a fast affine motion estimation(AME)calculation method based on statistical analysis is proposed.In the proposed method,we first abandon the integer pixel and 1/16-pixel accuracy,while retaining 1/4-pixel accuracy of the three motion vector(MV)accuracies.Secondly,we build the relationship between the iterations and quantization parameters(QP),slice type,and coding unit(CU)size to obtain an adaptive formula for reducing the number of iterations in AME.Then,the four integer pixels in the four corners of CU in the fine granularity search(FGS)algorithm are replaced by two diagonal sub pixels.Finally,the sum of absolute transform difference(SATD)cost is used to replace the rate distortion optimization(RDO)cost.Experimental results show that compared with the H.266/VVC reference software VTM-10.0,the proposed algorithm saves 8.34％and 8.83％of time in low delay B(LDB)and random access(RA)configurations,while the performance loss is only 0.10％and 0.12％,respectively.
Versatile video codingAffine motion estimationPixel accuracyFine granularity searchSum of absolute transform difference
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