Rate-Distortion Analysis of Optically Passive Vision Compression
The use of remote vision sensors for autonomous decision-making poses the challenge of transmitting high-volume visual data over resource-constrained channels in real-time. In robotics and control applications, many systems can quickly destabilize, which can exacerbate the issue by necessitating higher sampling frequencies. This work proposes a novel sensing paradigm in which an event camera observes the optically generated cosine transform of a visual scene, enabling high-speed, computation-free video compression inspired by modern video codecs. In this study, we simulate this optically passive vision compression (OPVC) scheme and compare its rate-distortion performance to that of a standalone event camera (SAEC). We find that the rate-distortion performance of the OPVC scheme surpasses that of the SAEC and that this performance gap increases as the spatial resolution of the event camera increases.