论文标题
基于AEGBM3D滤波器和后传播神经网络的H.265/SHVC的增强性能
An enhanced performance for H.265/SHVC based on combined AEGBM3D filter and back-propagation neural network
论文作者
论文摘要
本文介绍了最新的视频编码标准H265 SHVC，这是对高效率视频编码（HEVC）的可扩展扩展。 HEVC与其前身相比引入了新的编码工具，并且与所有类型的电子小工具向后兼容。由于传输带宽的限制是一个主要问题，因此无法提供具有不同显示功能的小工具。解决此问题的一种解决方案将是视频序列的压缩，该视频序列集中在本文中以保存或增加PSNR，同时还原位速率外，除了在SHVC编码器中实施的新方法外。这种新方法经历了合并的AEGBM3D（自适应边缘引导型键匹配和3D）滤波和背部传播技术。该技术包括一个避免空间冗余和降压帧的AEGBM3D滤波器；因此，实现了PSNR的增强。将视频的PSNR与设定的阈值PSNR进行比较，以通过重复AEGBM3D过滤将PSNR维持在阈值以上的PSNR。如果输入块不包含训练以识别的功能，则基于神经网络机器学习方法的BP技术会不断限制输出。对输出的这种频繁控制会产生很少的位。因此，减少了位量。模拟结果表明，与现有方法相比，该提出的技术在PSNR中的平均增量为0.16和0.25db，比特率的平均减少分别为1.5和2倍，比位速率分别为28％和37％。
This paper deals with the latest video coding standard H265 SHVC, a scalable extension to High Efficiency Video Coding (HEVC). HEVC introduces new coding tools compared to its predecessor and is backward compatible with all types of electronic gadgets. The gadgets with different display capabilities cannot be offered the same quality video due to the constraints in transmission bandwidth is a major problem. One solution to this problem will be the compression of the video sequence which is focused in this paper to preserve or increase PSNR while reducing bit-rate besides a novel method implemented in SHVC encoder. The novel method undergoes a combined AEGBM3D (adaptive edge guided block-matching and 3D) filtering and back-propagation technique. The technique includes an AEGBM3D filter which avoids spatial redundancy and de-noise frames; hence enhancement in PSNR is achieved. The obtained PSNR of the video is compared with the set threshold PSNR to maintain PSNR above the threshold by repeated AEGBM3D filtering. The BP technique based on the neural network machine learning approach continually restrains the output if the input block does not contain a feature they were trained to recognize. This frequent control over the output produces few bits; hence reduction in bit-rate is achieved. The simulation results show that the proposed technique delivers an average increment of 0.16 and 0.25dB in PSNR and an average decrement of 28 and 37% in bit-rate for 1.5 and 2 times spatial ratios respectively, compared with the existing methods.
