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    • 4. 发明授权
    • Method and apparatus for spatial class reduction
    • 用于空间分类减少的方法和装置
    • US06621936B1
    • 2003-09-16
    • US09250062
    • 1999-02-12
    • Tetsujiro KondoYasuhiro FujimoriSugata GhosalJames J. Carrig
    • Tetsujiro KondoYasuhiro FujimoriSugata GhosalJames J. Carrig
    • G06K940
    • G06T5/20
    • A method, apparatus, and article of manufacture for restoring a deteriorated signal to an undeteriorated signal. A deteriorated signal consists of a plurality of deteriorated and undeteriorated data points. For each deteriorated data point, a plurality of class types is created based upon characteristics of the area containing the deteriorated data point. The data point is classified with respect to one of the plurality of class types and assigned a corresponding input signal class. The undeteriorated signal is generated by adaptively filtering the deteriorated input signal in accordance with the input signal classification result. More than one classification method is used to create the plurality of class types. Created classes may include a motion class, an error class, a spatial class or a spatial activity class. A spatial class is modified according to a spatial symmetry.
    • 一种用于将恶化信号恢复到未衰减信号的方法,装置和制品。 恶化的信号由多个恶化和未经改进的数据点组成。 对于每个恶化的数据点,基于包含恶化的数据点的区域的特性来创建多个类类型。 数据点相对于多个类型之一被分类并分配相应的输入信号类。 通过根据输入信号分类结果对劣化输入信号进行自适应滤波,产生未衰减的信号。 使用多种分类方法来创建多个类类型。 创建的类可以包括运动类,错误类,空间类或空间活动类。 根据空间对称性修改空间类。
    • 6. 发明授权
    • Classified adaptive error recovery method and apparatus
    • 分类自适应误差恢复方法和装置
    • US06351494B1
    • 2002-02-26
    • US09405866
    • 1999-09-24
    • Tetsujiro KondoJames J. CarrigYasuhiro FujimoriWilliam Knox Carey
    • Tetsujiro KondoJames J. CarrigYasuhiro FujimoriWilliam Knox Carey
    • H04B166
    • H04N19/80H04N5/145H04N5/21
    • A method, apparatus, and article of manufacture for restoring a deteriorated signal to an undeteriorated signal. A deteriorated signal consists of a plurality of deteriorated and undeteriorated data points. For each deteriorated data point, a plurality of class types including a motion vector class is created based upon characteristics of the area containing the deteriorated data point. The data point is classified with respect to one of the plurality of class types and assigned a corresponding input signal class. The undeteriorated signal is generated by adaptively filtering the deteriorated input signal in accordance with the input signal classification result. More than one classification method is used to create the plurality of class types. Created classes may include a motion class, an error class, a spatial class, a spatial activity class, or a motion vector class.
    • 一种用于将恶化信号恢复到未衰减信号的方法,装置和制品。 恶化的信号由多个恶化和未经改进的数据点组成。 对于每个恶化的数据点,基于包含恶化的数据点的区域的特性来创建包括运动矢量类的多个类型。 数据点相对于多个类型之一被分类并分配相应的输入信号类。 通过根据输入信号分类结果对劣化输入信号进行自适应滤波,产生未衰减的信号。 使用多种分类方法来创建多个类类型。 创建的类可以包括运动类,错误类,空间类,空间活动类或运动矢量类。
    • 7. 发明授权
    • Method and apparatus for adaptive class tap selection according to
multiple classification
    • 根据多重分类的自适应类别抽头选择的方法和装置
    • US6151416A
    • 2000-11-21
    • US249735
    • 1999-02-12
    • Tetsujiro KondoYasuhiro FujimoriSugata GhosalJames J. Carrig
    • Tetsujiro KondoYasuhiro FujimoriSugata GhosalJames J. Carrig
    • G06T5/00G06T5/20H04N5/21H04N19/895G06K9/40H04N5/235
    • H04N5/21G06T5/20H04N19/503H04N19/80H04N19/895H04N19/98
    • A method, apparatus, and article of manufacture for restoring a deteriorated signal to an undeteriorated signal. A deteriorated signal consists of a plurality of deteriorated and undeteriorated data points. For each deteriorated data point, a plurality of class types is created based upon characteristics of the area containing the deteriorated data point. The data point is classified with respect to one of the plurality of class types and assigned a corresponding input signal class. The undeteriorated signal is generated by adaptively filtering the deteriorated input signal in accordance with the input signal classification result. More than one classification method is used to create the plurality of class types. Created classes may include a motion class, an error class, a spatial class or a spatial activity class. An adaptive class tap structure is used to create the plurality of class types for improvement of classification quality. The spatial class taps can be selected adaptively according to the motion and or error class. The spatial activity class taps can be selected adaptively according to the motion and or error class.
    • 一种用于将恶化信号恢复到未衰减信号的方法,装置和制品。 恶化的信号由多个恶化和未经改进的数据点组成。 对于每个恶化的数据点,基于包含恶化的数据点的区域的特性来创建多个类类型。 数据点相对于多个类型之一被分类并分配相应的输入信号类。 通过根据输入信号分类结果对劣化输入信号进行自适应滤波,产生未衰减的信号。 使用多种分类方法来创建多个类类型。 创建的类可以包括运动类,错误类,空间类或空间活动类。 使用自适应类抽头结构来创建用于提高分类质量的多个类类型。 可以根据运动和或误差等级自适应地选择空间类别抽头。 可以根据运动和或错误类自适应地选择空间活动类别抽头。
    • 8. 发明授权
    • Temporal classified filtering for video compression
    • 视频压缩的时域分类过滤
    • US08503530B2
    • 2013-08-06
    • US10856093
    • 2004-05-27
    • Zhourong MiaoJames J. Carrig, Jr.Marco Paniconi
    • Zhourong MiaoJames J. Carrig, Jr.Marco Paniconi
    • G06K9/40
    • H04N19/573H04N19/105H04N19/117H04N19/139H04N19/17H04N19/46H04N19/51H04N19/61H04N19/80
    • Temporal classified filtering encodes image data by applying filters assigned to classes of pixels in a target frame to predict values for the pixels. The pixels are classified based on their associated motion vectors and the motion vectors are used to position the filters on the reference frame. Prediction error values are also calculated. The filters, motion vectors, and prediction errors represent the pixels in the encoded image data. The reference frame may be a past or future frame of the image data, and multiple reference frames of various combinations of past and future frames may be used. The filters for multiple reference frames are three-dimensional comprising a two-dimensional filter for each reference frame. The filters may be pre-determined or generated as the frames are encoded. The image data is recreated by applying the filters to the reference frames and correcting the resulting predictions with the prediction error values.
    • 时间分类过滤通过应用分配给目标帧中的像素类的滤波来对图像数据进行编码,以预测像素的值。 基于它们相关联的运动矢量对像素进行分类,运动矢量用于将滤波器定位在参考帧上。 还计算预测误差值。 滤波器,运动矢量和预测误差表示编码图像数据中的像素。 参考帧可以是图像数据的过去或将来的帧,并且可以使用过去和未来帧的各种组合的多个参考帧。 用于多个参考帧的滤波器是三维的,其包括用于每个参考帧的二维滤波器。 当帧被编码时,滤波器可以被预先确定或生成。 通过将滤波器应用于参考帧并用预测误差值校正所得到的预测来重新创建图像数据。