Rate-Distortion Analysis of Optically Passive Vision Compression

TL;DR

This paper introduces an optically passive vision compression scheme using event cameras observing cosine transforms, achieving superior rate-distortion performance compared to standalone event cameras, especially at higher resolutions.

Contribution

The paper proposes a novel passive optical sensing paradigm for high-speed video compression using event cameras observing cosine transforms, improving rate-distortion performance.

Findings

OPVC surpasses SAEC in rate-distortion performance.

Performance gap widens with higher spatial resolution.

Simulation results validate the effectiveness of the proposed scheme.

Abstract

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.