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    • 2. 发明申请
    • HIERARCHICAL MOTION VECTOR PROCESSING METHOD, SOFTWARE AND DEVICES
    • 层次运动矢量处理方法,软件和设备
    • WO2009032255A3
    • 2009-05-07
    • PCT/US2008010334
    • 2008-09-03
    • UNIV CALIFORNIANGUYEN TRUONGHUANG AI-MEI
    • NGUYEN TRUONGHUANG AI-MEI
    • H04N7/26H04N7/24
    • H04N19/521H04N19/132H04N19/51H04N19/513H04N19/553H04N19/57H04N19/587H04N19/86
    • A preferred method for hierarchical motion vector processing determines reliability levels of blocks in image data according to residual energy levels. Macroblocks of an image frame are merged according to reliability levels of the motion vectors of blocks. Single motion vectors are selected for merged macroblocks. Motion vectors of blocks merged in the step of merging are iteratively assigned by minimizing the bi-directional prediction difference on successively smaller merged blocks. The reliability levels are preferably determined by measure residual energy of both chrominance and luminance components. In preferred embodiments, motion vector correlation is used to assist the MV reliability classification and the merging and iterative assignment. Refinement and smoothing can be conducted on successively finer block sizes. Additionally, preferred methods account for occlusions by choosing only one of forward or backward prediction for occlusion regions depending upon the class of the occlusion. Results of motion vector classification of the invention can be used in motion compensated frame interpolation and other techniques.
    • 用于分级运动矢量处理的优选方法根据剩余能量级别来确定图像数据中的块的可靠性级别。 图像帧的宏块根据块的运动矢量的可靠性级别进行合并。 为合并的宏块选择单个运动矢量。 在合并步骤中合并的块的运动矢量通过最小化连续较小的合并块上的双向预测差异来迭代地分配。 可靠性水平优选由色度和亮度分量的测量剩余能量确定。 在优选实施例中,使用运动矢量相关来辅助MV可靠性分类以及合并和迭代分配。 细化和平滑可以在更细的块大小上进行。 此外,优选的方法通过根据遮挡的类别仅选择遮挡区域的向前或向后预测中的一个来解决遮挡。 本发明的运动矢量分类的结果可以用于运动补偿帧插值和其他技术。
    • 4. 发明申请
    • GLOBAL MOTION ESTIMATION IMAGE CODING AND PROCESSING
    • 全球运动估计图像编码和处理
    • WO2005027491A3
    • 2007-02-01
    • PCT/US2004028334
    • 2004-09-01
    • UNIV CALIFORNIA
    • KUMAR SANJEEVNGUYEN TRUONGBISWAS MAINAK
    • G06K9/00H04N20060101
    • H04N19/521H04N19/527H04N19/53H04N19/547H04N19/61
    • The invention provides methods for global motion estimation, determining a coarse estimation (130), and refining a coarse estimation (150). Embodiments of the invention provide a fast and robust global motion estimation algorithm based on two-stage coarse-to-fine refinement strategy, which is capable of measuring large motions. An embodiment of the invention may be applied as a modification of any standard, e.g. MPEG-4 that uses the affine model of motion estimation. Embodiments of the invention may be used in the six parameter affine motion model, and other embodiments of the invention are applicable to the two parameter translation model, the four parameter RST model, and the eight parameter projective model. In a preferred embodiment, a coarse estimation is developed in a translation invariant domain (130), and then is refined in the spatial domain (150).
    • 本发明提供了全局运动估计的方法,确定粗略估计(130),以及细化粗估计(150)。 本发明的实施例提供了一种基于能够测量大运动的两阶段粗到细精细化策略的快速且鲁棒的全局运动估计算法。 本发明的实施例可以应用于任何标准的修改,例如, MPEG-4使用运动估计的仿射模型。 本发明的实施例可以用于六参数仿射运动模型,本发明的其它实施例可应用于两个参数翻译模型,四个参数RST模型和八个参数投影模型。 在优选实施例中,在翻译不变域(130)中形成粗略估计,然后在空间域(150)中进行细化。