发明名称 Video compression using multiple variable length coding methods for multiple types of transform coefficient blocks
摘要 Classifying a series of quantized transform coefficients of a block of image data into one of a pre-defined plurality of classes for entropy coding, and entropy coding the block. A class is defined by at least the size of the block and typically but not necessarily one or more other factors. The classified series is coded by one of a set of pre-defined entropy coding methods, e.g., variable length coding methods for the pre-defined classes.
申请公布号 US9338478(B2) 申请公布日期 2016.05.10
申请号 US201414578304 申请日期 2014.12.19
申请人 Cisco Technology, Inc. 发明人 Chen Wen-hsiung;Xu Yian
分类号 H04N19/176;H04N19/91;H03M7/40;H04N19/46;H04N19/13;H04N19/134;H04N19/124;H04N19/60 主分类号 H04N19/176
代理机构 代理人
主权项 1. A method of processing, comprising: obtaining an ordered series of quantized transform coefficients of a block of image data; classifying the ordered series of quantized transform coefficients in order to produce a classified series characterized by one or more pre-defined classes, wherein classification occurs at least in accordance with the size of the block of image data, the classifying including: first-stage classifying the ordered series of quantized transform coefficients in order to produce a first-stage classified series having a first class of a plurality of pre-defined first classes, the first-stage classifying being according to the size of the block, andsecond-stage classifying the first-stage classified series in order to produce a classified series having the first class and further having a second class of one or more second classes pre-defined for the first class; and applying an entropy coding method to the ordered series of quantized transform coefficients in order to generate a sequence of codewords, wherein for at least two different pre-defined classes of ordered series of different sizes, different pre-defined entropy coding methods are applied to the different pre-defined classes.
地址 San Jose CA US