LAUSR

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.