The letter introduces an efficient context-based lossless image codec for encoding event camera frames. The asynchronous events acquired by an event camera in a spatio-temporal neighborhood are collected by an Event Frame (EF). A more efficient way to store the event data is introduced, where up to eight EFs are represented as a pair of an event map image (EMI), containing the spatial information, and a vector, containing the polarity information. The proposed codec encodes the EMI using: (i) a binary map, which signals the positions where at least one event occurs in the EFs; (ii) the number of events for each signalled position; and (iii) their EF index. Template context modelling and adaptive Markov modelling are employed to encode these three types of data. The experimental evaluation for EFs generated at different time intervals demonstrates that the proposed method achieves an improved performance compared with both video coding standards, HEVC and VVC, and state-of-the-art lossless image coding methods, CALIC and FLIF. When all events are collected by EFs, a relative compression of up to 5.8 is achieved compared with the raw event encapsulation provided by the event camera.

中文翻译：

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事件摄像机帧的无损压缩

这封信介绍了一种高效的基于上下文的无损图像编解码器，用于对事件摄像机帧进行编码。事件相机在时空邻域中获取的异步事件由事件框架（EF）收集。介绍了一种更有效的事件数据存储方式，其中多达 8 个 EF 被表示为一对包含空间信息的事件映射图像 (EMI) 和一个包含极性信息的矢量。建议的编解码器使用以下方法对 EMI 进行编码：(i) 一张二进制地图，表示在 EF 中至少发生一个事件的位置；(ii) 每个信号仓位的事件数量；和(iii) 他们的 EF 指数。模板上下文建模和自适应马尔可夫建模用于对这三种类型的数据进行编码。对在不同时间间隔生成的 EF 的实验评估表明，与视频编码标准 HEVC 和 VVC 以及最先进的无损图像编码方法 CALIC 和 FLIF 相比，所提出的方法实现了改进的性能。当 EF 收集所有事件时，与事件摄像机提供的原始事件封装相比，可实现高达 5.8 的相对压缩。