Memory-Efficient Fixed-Length Representation of Synchronous Event Frames for Very-Low-Power Chip Integration - Schiopu, Ionut; Bilcu, Radu Ciprian (Electronics (Basel), 2023)
The new event cameras are now widely used in many computer vision applications. Their high raw data bitrate levels require a more efficient fixed-length representation for low-bandwidth transmission from the event sensor to the processing chip. A novel low-complexity lossless compression framework is proposed for encoding the synchronous event frames (EFs) by introducing a novel memory-efficient fixed-length representation suitable for hardware implementation in the very-low-power (VLP) event-processing chip. A first contribution proposes an improved representation of the ternary frames using pixel-group frame partitioning and symbol remapping. Another contribution proposes a novel low-complexity memory-efficient fixed-length representation using multi-level lookup tables (LUTs). Complex experimental analysis is performed using a set of group-size configurations. For very-large group-size configurations, an improved representation is proposed using a mask-LUT structure. The experimental evaluation on a public dataset demonstrates that the proposed fixed-length coding framework provides at least two times the compression ratio relative to the raw EF representation and a close performance compared with variable-length video coding standards and variable-length state-of-the-art image codecs for lossless compression of ternary EFs generated at frequencies bellow one KHz. To our knowledge, the paper is the first to introduce a low-complexity memory-efficient fixed-length representation for lossless compression of synchronous EFs, suitable for integration into a VLP event-processing chip.