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    • 3. 发明申请
    • REUSE OF A SEARCH REGION IN MOTION ESTIMATION OF MULTIPLE TARGET FRAMES
    • 多个目标框架的运动估计搜索区域的重用
    • US20100309981A1
    • 2010-12-09
    • US12477963
    • 2009-06-04
    • SOYEB NAGORIArun Shankar KudanaAjit Venkat Rao
    • SOYEB NAGORIArun Shankar KudanaAjit Venkat Rao
    • H04N7/26
    • H04N19/57H04N19/423H04N19/43H04N19/61
    • Several methods and a system to reuse a search region in motion estimation of multiple target frames are disclosed. In an embodiment, a method includes acquiring a search region of a reference frame. The method also includes maintaining the search region in a memory. In addition, the method includes performing motion estimation of a macroblock of a target frame in a direction using a processor and the search region. The method also includes reusing the search region maintained in the memory to perform motion estimation of an additional macroblock of an additional target frame in an additional direction. The method may include reusing the search region maintained in the memory to perform motion estimation of a separate macroblock of a separate target frame in a separate direction.
    • 公开了在多个目标帧的运动估计中重用搜索区域的几种方法和系统。 在一个实施例中,一种方法包括获取参考帧的搜索区域。 该方法还包括将搜索区域保持在存储器中。 此外,该方法包括使用处理器和搜索区域在方向上执行目标帧的宏块的运动估计。 该方法还包括重新使用保持在存储器中的搜索区域,以在附加方向上执行附加目标帧的附加宏块的运动估计。 该方法可以包括重新使用保持在存储器中的搜索区域来执行单独目标帧在单独方向上的单独宏块的运动估计。
    • 6. 发明授权
    • Lossy compression technique for video encoder bandwidth reduction using compression error data
    • 使用压缩误差数据的视频编码器带宽降低的有损压缩技术
    • US08443275B2
    • 2013-05-14
    • US12211830
    • 2008-09-17
    • Ajit Deepak GupteMahesh Madhukar MehendaleHetul SanghviAjit Venkat Rao
    • Ajit Deepak GupteMahesh Madhukar MehendaleHetul SanghviAjit Venkat Rao
    • G06F7/02
    • H04N19/00763H04N19/428H04N19/433H04N19/593H04N19/61
    • A method, system and apparatus of lossy compression technique for video encoder bandwidth reduction using compression error data are disclosed. In one embodiment, a method includes storing an error data from a compression of an original reference data in an off-chip memory, accessing the error data during a motion compensation operation, and performing the motion compensation operation by applying the error data through an algorithm (e.g., determined by the method of storing the error data). The method may include generating a predicted frame in the motion compensation operation using a motion vector and an on-chip video data. In addition, the method may include determining the error data as a difference between a compressed reference data (e.g., is created by compressing the original reference data) and an original reference data (e.g., reconstructed from a prior predicted frame and a decompressed encoder data).
    • 公开了使用压缩误差数据的视频编码器带宽减小的有损压缩技术的方法,系统和装置。 在一个实施例中,一种方法包括将来自原始参考数据的压缩的错误数据存储在片外存储器中,在运动补偿操作期间访问错误数据,以及通过算法应用错误数据来执行运动补偿操作 (例如,通过存储错误数据的方法确定)。 该方法可以包括使用运动矢量和片上视频数据在运动补偿操作中生成预测帧。 此外,该方法可以包括将误差数据确定为压缩参考数据(例如,通过压缩原始参考数据产生)与原始参考数据之间的差异(例如,从先前预测帧和解压缩编码器数据重建 )。
    • 10. 发明授权
    • Variable dimension vector quantization
    • 可变维矢量量化
    • US5890110A
    • 1999-03-30
    • US411436
    • 1995-03-27
    • Allen GershoAmitava DasAjit Venkat Rao
    • Allen GershoAmitava DasAjit Venkat Rao
    • G10L19/00G10L19/02G10L5/06H04B1/66
    • G10L19/02
    • A variable dimension vector quantization method that uses a single "universal" codebook. The method can be given the interpretation of sampling full-dimensioned codevectors in the universal codebook and generating subcodevectors of the same dimension as input data subvector, which dimension may vary in time. A subcodevector is selected from the codebook to have minimum distortion between it and the input data subvector. The subcodevector with minimum distortion corresponds to the representative, full-dimensioned codevector in the codebook. The codebook is designed by inverse sampling of training subvectors to obtain full-dimension vectors, then iteratively clustering the training set until a stable centroid vector is obtained.
    • 使用单个“通用”码本的可变维度向量量化方法。 该方法可以给出通用码本中采样全尺寸代码矢量的解释,并生成与输入数据子向量相同维度的子代码矢量,该维度可能随时间变化。 从码本中选择一个子代码向量,使其与输入数据子向量之间具有最小的失真。 具有最小失真的子码矢量对应于码本中的代表性的,全尺寸的码矢量。 该码本是通过对训练子向量进行逆采样来设计的,以获得全维向量,然后迭代地聚类训练集,直到获得稳定的质心向量。