共查询到18条相似文献,搜索用时 546 毫秒
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文章提出了一种快速的DCT域MPEG-2到MPEG-1准卷积下呆样算法。在转码过程中。头信忠保持不变,且要求将每四个相邻MPEG-2宏块变为一个下采样MPEG-1宏块:用最大最小距离方法确定下采样宏块的运动向量、用简单多数原则确定下采样宏块类型以及用加全平均方案确定下呆样宏块的量化参数。另外,对下采样视频转码失真来源进行了分析。实验结果表明我们提出的转码方案,在同样条件下与级联像素域转码器(TM5)相比,不仅其计算复杂性减少67.6%、PNSR提高0.1dB,而且具有很小的比特控制错误。 相似文献
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DCT域快速下采样运动向量滤波器 总被引:1,自引:1,他引:0
目前的视频压缩标准多数采用DCT变换编码和运动补偿技术。运动估计约占整个编码时间的60%、运动补偿约占10%。所以在视频转码中,运动向量的再使用技术是十分重要的,目前较好的方法是欧氏最小距离方法,它的主要缺点是估计精度不高,本文对此进行了改进,提出了DCT、域快速下采样运动向量滤波器,其重建图像的峰值信噪声比Shanableh等人提出的方法平均高0.2dB。 相似文献
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提出了一种新DCT域任意m:n比率的下采样方法,即直接找出输入m^2个块与下采样输出的n^ 2个的块的DCT系数关系式。实验结果表明:本方法的重构图像的峰值信噪比(PNSR)优于Park方法0.5dB,且有较低的计算复杂性,适用于任何基于DCT压缩的视频转码方案。 相似文献
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根据MPEG-2与先进音视频编码(AVS,Advanced Coding of Audio and Video)标准在帧内预测中的不同点,介绍了一种基于变换域的帧内预测转码算法。新算法提出一种新的变换域转码结构,通过矩阵变换计算出AVS帧内预测的各种模式所对应的离散余弦变换(DCT,Discrete Cosine Transform)预测矩阵,推导出DCT域到AVS整数变换域的系数转换矩阵,同时给出DCT域内预测矩阵转换所需的运算量。实验结果表明,提出的帧内预测转换方法可以使计算复杂度降低50%,达到实时转码的要求。 相似文献
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Shizhong Liu Alan C. Bovik 《Journal of Visual Communication and Image Representation》2005,16(6):643-667
Video transcoding is a key technology to support video communications over heterogeneous networks. Although quite a bit of research effort has been made in video transcoding due to its wide applications, most video transcoding techniques proposed in the literature are optimized based on the simple mean squared error (MSE) metric which does not correlate well with the human visual perception. In this paper, foveation, a property of the HVS, is exploited in video transcoding. The proposed foveation embedded DCT domain video transcoding can reduce the bit rate without compromising visual quality or achieve better subjective quality for a given bit rate by shaping the compression distortion according to the foveated contrast sensitivity function of the HVS. In addition, fast algorithms for video foveation filtering and DCT domain inverse motion compensation are developed, which significantly improve the efficiency of video transcoding. 相似文献
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《Signal Processing: Image Communication》2006,21(1):44-58
To achieve portability between different kinds of encoding formats and network environments, heterogeneous video transcoding becomes a key technique for reducing the bitrate of a previously compressed video signal. A frame-skipping transcoder is often used to avoid an unacceptable picture quality when high transcoding ratio is required. Due to high computational complexity and quality degradation introduced by conventional frame-skipping transcoders, a DCT-based video frame-skipping transcoder has been proposed recently. However, the transcoding process of the motion compensated macroblocks in the DCT domain becomes the bottleneck since IDCT and DCT processes are required. In this paper, we propose a new architecture of the frame-skipping transcoder to reduce the computational complexity of motion compensated macroblocks in the frame-skipping process. The new architecture transcodes the dominant region of a motion compensated macroblock in the DCT domain by making use of the DCT coefficients of the incoming bistream and some pre-computed shift operators. By using a shifted version of the dominant vector, the re-encoding error introduced in the dominant region can be avoided. On the other hand, an adaptive transcoding architecture to transcode the boundary regions of MC marcoblocks and a way to perform error compensation are proposed. This architecture can further speed up the transcoding process of the motion compensated macroblocks. Half pixel accuracy related to our proposed frame skipping transcoder is also addressed. Experimental results show that, as compared to the conventional or DCT-based transocders, the new architecture is more robust to noise, gives rise to fewer requantization errors, and requires simple computational complexity. 相似文献
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视频转码是个复杂的过程,它需要对已经压缩过的码流进行解析,然后经过处理转换成满足解码终端要求的目标格式码流。为了提高视频转码的效率并降低视频转码的计算复杂度,根据视频转码的要求和图形处理器的并行结构,提出了一种利用GPU强大的并行计算能力来加速视频转码的算法。该算法将视频转码过程中耗时最多、最复杂的运动估计和模式选择过程转移到GPU上并行执行。在开发GPU通用计算能力的时候,采用NVIDIA公司的CUDA(统一计算设备架构)计算平台。实验结果证明,该算法可以有效提高视频转码的速度和效率。 相似文献
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《Signal Processing: Image Communication》2004,19(1):47-65
Video transcoding is a popular technique for adapting the bit-rate or spatial/temporal resolution of a precoded video to suit better the constraints and requirements of different transmission networks and receiving devices. To minimize computational complexity, many fast methods have been proposed to obtain the motion vectors required for transcoding a precoded video through reducing its frame size by an integral factor. In this paper, we extend the existing work by developing and comparing several fast methods of downsizing precoded videos by a rational factor. Methods that outperform others under different conditions or with different computational requirements are identified, and an application scenario that can benefit from the proposed rational downsizing video transcoding is presented. An efficient scheme is also proposed to select the proper reduced frame size for sustaining the best possible video quality at a specified lower bit-rate. The superiority of the proposed transcoding approach in comparison with the existing integral downsizing video transcoding or cascaded video re-encoding methods is evident from the experimental results shown in this paper. 相似文献
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提出一种基于输入码流信息和已转码码流信息的视频转码快速运动估计算法。本算法利用Alpha-激励均值滤波通过输入码流的运动矢量合成作为备选预测运动矢量之一,并利用H.264标准中帧间预测的方法通过已转码码流信息合成另一个备选预测运动矢量,共同作为EPZS运动估计算法的预测中心。结合图像的运动活跃性.自适应的调整运动估计的搜索策略。该算法比传统的运动矢量方法相比提高了1dB左右的PSNR,保持了较高的转码图像质量并与菱形搜索算法相比能够降低18%左右的转码时间。 相似文献
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《Digital Communications & Networks》2021,7(4):598-604
Video transcoding is to create multiple representations of a video for content adaptation. It is deemed as a core technique in Adaptive BitRate (ABR) streaming. How to manage video transcoding affects the performance of ABR streaming in various aspects, including operational cost, streaming delays, Quality of Experience (QoE), etc. Therefore, the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming services. These problems become more worthy of investigation with the emergence of the edge-cloud continuum, which makes the resource allocation for video transcoding more complicated. To this end, this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming, including designing a rate profile for video transcoding, providing resources for video transcoding in clouds, and caching multi-bitrate video contents in networks, etc. We analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service (QoS) optimization problems. The goal is to minimize resource consumption while guaranteeing the QoS for ABR streaming. We also discuss some promising research directions for the ABR streaming services. 相似文献