HEVC编码的泰勒率失真权衡与自适应块搜索

R. Anitha Kumari, A. Udupa
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引用次数: 0

摘要

高效视频编码(High efficiency video coding, HEVC)的发展适应于定义下一代压缩模型,以在不影响图像质量的情况下提供有效的压缩。HEVC比现有的压缩模型提供了更好的性能。这项工作通过提出加权熵编码和基于率失真(R-D)权衡的自适应块搜索,开发了一种视频压缩方法。利用泰勒级数设计了一种新的R-D权衡,称为泰勒R-D权衡。提出了自适应块搜索算法,利用基于六边形的树搜索算法(HBTSA)选择最优块,并结合泰勒R-D权衡,启动视频编码中运动估计的块搜索过程。最初,帧是从输入视频中抽取的。然后,将视频帧分割成宏块进行自适应块搜索。此外,通过加权上下文自适应二进制算术编码(CABAC)选择合适的块并将其分配到编码过程中,该编码采用加权熵函数来保持压缩后的视频质量。结果表明,在足球、海岸警卫队、花园和网球运动中,所提出的HBTSA方法的PSNR和SSIM分别为42.717dB和0.991。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Taylor Rate-Distortion trade-off and Adaptive block search for HEVC Encoding
The advancement in High efficiency video coding (HEVC) is adapted for defining the subsequent generation compression model for offering efficient compression without affecting the image quality. The HEVC offers improved performance than the existing compression models. This work develops an approach for video compression by proposing weighted entropy coding and adaptive block search based Rate-Distortion (R-D) trade-off. A new R-D trade-off, named Taylor R-D trade-off, is designed using Taylor series. The adaptive block search algorithm is proposed for initiating the block search process of motion estimation in video coding by selecting the optimal block using the Hexagon Based Tree Search Algorithm (HBTSA), along with the Taylor R-D trade-off. Initially, the frames are extorted from the input video. Then, the video frames are divided into macroblocks to perform the adaptive block search. Further, the suitable blocks are selected and given to the encoding process by weighted Context-Adaptive Binary Arithmetic Coding (CABAC) that employs a weighted entropy function to persist the video quality after the compression. The results evaluate that the proposed HBTSA method shows improved PSNR and SSIM using Football, coast guard, garden, and, tennis with values 42.717dB, and 0.991, respectively.
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