Dynamic Bandwidth Allocation for Hybrid Event-RGB Transmission
Journal:
arXiv
Published Date:
Jun 25, 2025
Abstract
Event cameras asynchronously capture pixel-level intensity changes with
extremely low latency. They are increasingly used in conjunction with RGB
cameras for a wide range of vision-related applications. However, a major
challenge in these hybrid systems lies in the transmission of the large volume
of triggered events and RGB images. To address this, we propose a transmission
scheme that retains efficient reconstruction performance of both sources while
accomplishing real-time deblurring in parallel. Conventional RGB cameras and
event cameras typically capture the same scene in different ways, often
resulting in significant redundant information across their outputs. To address
this, we develop a joint event and image (E-I) transmission framework to
eliminate redundancy and thereby optimize channel bandwidth utilization. Our
approach employs Bayesian modeling and the information bottleneck method to
disentangle the shared and domain-specific information within the E-I inputs.
This disentangled information bottleneck framework ensures both the compactness
and informativeness of extracted shared and domain-specific information.
Moreover, it adaptively allocates transmission bandwidth based on scene
dynamics, i.e., more symbols are allocated to events for dynamic details or to
images for static information. Simulation results demonstrate that the proposed
scheme not only achieves superior reconstruction quality compared to
conventional systems but also delivers enhanced deblurring performance.
