Bricker to BRACE: A Bracket Exposure RAW Dataset and Restoration Model for Flicker-Banding

2026-06-29

AI Summary

This work addresses flickering banding artifacts in screen-captured images—manifesting as color shifts and jagged distortions—caused by temporal aliasing between rolling shutters and display brightness modulation. The study is the first to reveal the high sensitivity of these artifacts to exposure parameters and proposes a restoration framework leveraging multi-frame exposure-bracketed RAW data. Key contributions include the Bricker dataset, which combines physics-based simulation with automated real-world acquisition; a frequency-aware banding prior; and a Multi-Scale Cross-Attention Modulator (MSCAM). Additionally, a novel Stripe Frequency Consistency metric is introduced for quantitative evaluation. The proposed BRACE model consistently outperforms existing methods on both synthetic and real-world data, effectively suppressing banding artifacts and enhancing image fidelity. All resources are publicly released.

Abstract

Flicker-banding (FB), arises from temporal aliasing between a camera's rolling shutter and a display's brightness modulation, degrading screen-captured image readability with color shifts and jagged patterns. Existing single-frame methods with simplified parametric stripe models cannot reliably distinguish these artifacts from genuine texture. To address this, we conduct a systematic analysis of complex FB morphologies and reveal their significant variation across exposure settings, motivating a multi-frame bracketed RAW restoration paradigm. We construct Bricker, a synthetic-real bracketed RAW dataset built via ray-tracing-based physical simulation and automated multi-exposure capture tool. We further propose BRACE: Bracketed RAW Flicker-Banding Removal, a multi-frame restoration model that utilizes frequency-aware banding prior and a multi-scale spatial cross-attention modulator (MSCAM) for cross-exposure spatial fusion. We also introduce the Stripe Frequency Consistency (SFC) metric to evaluate banding removal. Experiments demonstrate state-of-the-art performance on both synthetic and real benchmarks. Our dataset and code are available at: https://github.com/ZZH-qwq/BRACE.

Problem

• flicker-banding
• temporal aliasing
• rolling shutter
• display brightness modulation
• image artifacts

Innovation

• flicker-banding
• bracketed RAW
• multi-frame restoration
• spatial cross-attention
• Stripe Frequency Consistency