Efficient Fixed-Point Implementation Of Matrix-Based Intra Prediction

In the current version of the evolving Versatile Video Coding (VVC) standard, the Matrix-Based Intra Prediction (MIP) tool is included which is based on data-driven training techniques. This paper describes how an efficient fixed point implementation of the MIP prediction modes was designed. First, a method is presented that improves the integer quantization of the floating-point matrices resulting from the training by geometrically transforming the input and output. Second, a soft-clipping function can be used during the training stage to restrict the range of floating-point matrix entries. This enables the quantization of the trained coefficients with a fixed bit depth and precision. The clipping itself has no impact on the compression efficiency. The obtained predictors are incorporated into the Versatile Video Coding Test Model 7. All-Intra bit-rate savings of 0.6 % across different resolutions in terms of the Bjøntegaard-Delta bit rate (BD-rate) are reported.