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基于样本的VVC无损帧内梯度预测算法

Sample-based VVC Lossless Intra Gradient Prediction Algorithm

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为了进一步提升VVC无损帧内编码的性能,在BDPCM编码工具的基础上,利用样本之间的关系,对其进行改进,提出了一种基于样本的梯度预测(Sample-based Gradient Prediction,SGP)算法.在该算法中,预测样本由对应预测方向上的相邻参考样本,以及参考样本之间的梯度信息获得,获得的预测样本被限制在一定范围内.在VVC测试模型(VTM)12.3上的实验结果表明,提出的SGP算法在VVC无损帧内编码中平均节省了 5.30%的比特率,编码时间增加了17.7%,解码时间下降了 19.5%.相较于BDPCM可以达到的3.88%平均比特率节省,SGP所带来的比特率节省大幅度提升,并且编码时间和解码时间都更短.
In order to further improve the performance of VC lossless intra coding,this paper improves on the BDPCM coding tool by utilizing the relationships between samples and proposes a sample-based gradient prediction(SGP)algo-rithm.In this algorithm,the prediction samples are obtained from adjacent reference samples in the corresponding predic-tion direction and the gradient information between the reference samples,and the obtained prediction samples are limited to a certain range.The experimental results on the VVC test model(VTM)12.3 reveal that the proposed SGP algorithm can save 5.30%bit-rate on average in VVC lossless intra coding.The encoding time is increased by 17.7%,and the decoding time is decreased by 19.5%.Compared to BDPCM,which achieves 3.88%average bit-rate savings,the bit-rate savings brought by SGP are significantly improved,and the encoding time and the decoding time are both shorter.

image codinglossless compressionintra predictiongradient predictionversatile video coding(WC)

陈国捷

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上海大学通信与信息工程学院,上海 200444

图像编码 无损压缩 帧内预测 梯度预测 通用视频编码(VVC)

国家重点研发计划

2019YFB2204500

2024

工业控制计算机
中国计算机学会工业控制计算机专业委员会 江苏省计算技术研究所有限责任公司

工业控制计算机

影响因子:0.258
ISSN:1001-182X
年,卷(期):2024.37(1)
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