ER-Diff: A Multi-Scale Exposure Residual-Guided Diffusion Model for Image Exposure Correction
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Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
This paper proposes an Exposure Residual-guided Diffusion Model (ER-Diff) to address the performance limitations of existing image restoration methods in handling non-uniform exposure. Current exposure correction techniques struggle with detail recovery in extreme over/underexposed regions and global exposure balancing. While diffusion models offer powerful generative capabilities for image restoration, effectively leveraging exposure information to guide the denoising process remains underexplored. Additionally, content reconstruction fidelity in severely degraded regions is challenging to ensure. To tackle these issues, ER-Diff explicitly constructs exposure residual features to guide the diffusion process. Specifically, we design a multi-scale exposure residual guidance module that first computes the residual between the input image and an ideally exposed reference, then transforms it into hierarchical feature representations via a multi-scale extraction network, and finally integrates these features progressively into the denoising process. This design enhances feature representation in locally distorted exposure areas while maintaining global exposure consistency. By decoupling content reconstruction and exposure correction, our method achieves more natural exposure adjustment with better detail preservation while ensuring content authenticity. Extensive experiments demonstrate that ER-Diff outperforms state-of-the-art exposure correction methods in both quantitative and qualitative evaluations, particularly in complex lighting conditions, effectively balancing detail retention and exposure correction.
Description
CCS Concepts: Computing methodologies → Exposure Correction ; Diffusion Models; Multi-scale Residual Guidance
@inproceedings{10.2312:pg.20251276,
booktitle = {Pacific Graphics Conference Papers, Posters, and Demos},
editor = {Christie, Marc and Han, Ping-Hsuan and Lin, Shih-Syun and Pietroni, Nico and Schneider, Teseo and Tsai, Hsin-Ruey and Wang, Yu-Shuen and Zhang, Eugene},
title = {{ER-Diff: A Multi-Scale Exposure Residual-Guided Diffusion Model for Image Exposure Correction}},
author = {Chen, TianZhen and Liu, Jie and Ru, Yi},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-295-0},
DOI = {10.2312/pg.20251276}
}