AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices

TL;DR

AdaEnlight is a mobile system that enhances low-light videos in real-time while adapting to energy constraints, balancing visual quality and power efficiency for on-device applications.

Contribution

It introduces an energy-aware low-light video enhancement system that adapts runtime behavior to energy budgets, suitable for mobile devices.

Findings

Achieves real-time enhancement with competitive visual quality.

Demonstrates adaptability to dynamic energy budgets.

Outperforms state-of-the-art low-light enhancement solutions.

Abstract

The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device processing of video streams to deliver real-time, high-quality services for privacy and robustness concerns. However, the performance of these applications is constrained by the raw video streams, which tend to be taken with small-aperture cameras of ubiquitous mobile platforms in dim light. Despite extensive low-light video enhancement solutions, they are unfit for deployment to mobile devices due to their complex models and and ignorance of system dynamics like energy budgets. In this paper, we propose AdaEnlight, an energy-aware low-light video stream enhancement system on mobile devices. It achieves real-time video enhancement with competitive visual quality while allowing runtime behavior adaptation to the platform-imposed dynamic energy budgets. We report extensive experiments on diverse datasets, scenarios, and platforms and demonstrate the superiority of AdaEnlight compared with state-of-the-art low-light image and video enhancement solutions.