Lossless Video Coding Based On Probability Model Optimization With Improved Adaptive Prediction
Kyohei Unno, Yusuke Kameda, Yasuyo Kita, Ichiro Matsuda, Susumu Itoh, Kei Kawamura
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We previously proposed a novel lossless coding method that utilizes example search and adaptive prediction within a framework of probability model optimization for monochrome video. In this paper, we improve the adaptive prediction in terms of coding performance and processing time. More precisely, we made modifications to the following three items: (a) reference pel arrangements, (b) motion vector derivation, and (c) optimal selection of predictors. Experimental results show that the proposed method certainly improves the coding performance and the processing time compared to our previous method, and achieves better coding performance than the VVC-based lossless video coding scheme.