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Lossy compression for images and signals by identifying regions with low density of features

机译:通过识别特征密度低的区域来对图像和信号进行有损压缩

摘要

A device, system, and method perform lossy compression for images and signals by identifying regions with a low density of features. The method performed at a sensor communicatively connected to a receiver includes capturing sensor data. The method includes selecting a position in the sensor data. The method includes determining a local entropy of the position based on an entropy operation that indicates a probability distribution of a plurality of available values. When the local entropy is below a predetermined threshold, the method includes applying a first pre-processing operation to the position that averages features included in the position. The method includes transmitting the pre-processed sensor data corresponding to the position to the receiver.
机译:一种设备,系统和方法,通过识别特征密度低的区域,对图像和信号执行有损压缩。在通信地连接到接收器的传感器处执行的方法包括捕获传感器数据。该方法包括选择传感器数据中的位置。该方法包括基于熵操作来确定位置的局部熵,该熵操作指示多个可用值的概率分布。当局部熵低于预定阈值时,该方法包括将第一预处理操作应用于对该位置进行平均的位置。该方法包括将与该位置相对应的预处理传感器数据发送到接收器。

著录项

  • 公开/公告号US10728420B2

    专利类型

  • 公开/公告日2020-07-28

    原文格式PDF

  • 申请/专利权人 WIND RIVER SYSTEMS INC.;

    申请/专利号US201815950919

  • 发明设计人 IONUT POPA;

    申请日2018-04-11

  • 分类号G06K9;H04N1/41;H04N19/13;H04N19/80;H03M7/30;

  • 国家 US

  • 入库时间 2022-08-21 11:28:08

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