精品文档---下载后可任意编辑H.264 帧内预测算法讨论的开题报告摘要随着数字视频技术的迅速进展和广泛应用，视频编码已成为多媒体系统中最关键和最重要的部分之一。H.264 编码标准极大地提高了视频压缩率和图像质量，成为目前最先进的视频编码标准之一。其中最重要的编码技术之一是帧内预测。本文将重点讨论 H.264 帧内预测算法，探究其优化方法及性能提升。本文首先对 H.264 编码标准以及帧内预测算法进行了介绍，包括预测模式、运动估量和量化和熵编码等基础知识。然后对现有的帧内预测算法进行了综述和总结，包括多项式拟合法、插值法等。针对帧内预测算法存在的问题和不足，本文提出了基于深度学习方法的优化方案，即使用卷积神经网络（CNN）对预测残差进行学习和预测，以提高预测的准确性和稳定性。本文将采纳 C 语言进行编程实现，并选用一组标准视频测试集进行实验验证。本文的讨论成果将为 H.264 编码标准的应用和进展提供参考，同时可以为增强视频压缩和图像质量提供有效的技术支持。关键词：H.264 视频编码；帧内预测；深度学习；卷积神经网络；视频压缩AbstractWith the rapid development and widespread application of digital video technology, video coding has become one of the most critical and important parts in multimedia systems. H.264 encoding standard greatly improves video compression rate and image quality, and has become one of the most advanced video coding standards. One of the most important encoding techniques is intra-frame prediction. This paper focuses on the study of H.264 intra-frame prediction algorithm, exploring its optimization methods and performance improvement.This paper first introduces the H.264 encoding standard and intra-frame prediction algorithm, including prediction mode, motion estimation, and quantization and entropy coding and other basic knowledge. Then, the existing intra-frame prediction algorithms are reviewed and summarized, including polynomial fitting method, interpolation method, etc. In view of the problems and shortcomings of intra-frame prediction algor...
