Entropy Coding-based Lossless Compression of Asynchronous Event Sequences

Neuromorphic Vision Data Coding: Classifying and Reviewing

“…Please recall that, as in [28] and [30], the input to the conventional image/video coding solutions are (event) images obtained by combining, through some mathematical function, the information enclosed in each group of 5 (consecutive) EFs (please refer to [28] for more details). [35] Still in 2023, Schiopu and Bilcu extended the low-complexity lossless coding framework in [32] (denominated LLC-ARES), by modifying the TTP algorithm to employ entropy coding based techniques, to code the same-timestamp (ST) representation of event data generated from a DVS-like sensor (consisting of location, polarity, and timestamp) [35].…”

“…Temporal error metrics have also been proposed for the same event-/spike-based NDVC solutions ( [23], [26] and [27]) to measure the temporal distortion.  Average event/EF encoding/decoding speed may also be found in the performance evaluation of some eventbased NVDC solutions, notably the ones that target to be suitable for hardware implementation in low-power/lowcost event signal processing chips, e.g., [30], [32], [34] and [35]; in those solutions, it is also possible to find other event related performance assessment metrics such as the average event size and the average encoded event rate. It is important to note that all these metrics, except the average event size, are dependent on the hardware platform used which makes comparison rather difficult.…”