WEC-DG: Multi-Exposure Wavelet Correction Method Guided by Degradation Description

TL;DR

This paper introduces WEC-DG, a wavelet-based multi-exposure correction method with degradation guidance, improving image brightness, contrast, and detail recovery under complex lighting conditions.

Contribution

The paper proposes a novel wavelet-based exposure correction framework with degradation guidance and light-detail decoupling, enhancing adaptability and accuracy in diverse imaging environments.

Findings

Outperforms existing algorithms on public datasets.

Achieves significant improvements in exposure correction quality.

Effectively handles intra-class variability in lighting conditions.

Abstract

Multi-exposure correction technology is essential for restoring images affected by insufficient or excessive lighting, enhancing the visual experience by improving brightness, contrast, and detail richness. However, current multi-exposure correction methods often encounter challenges in addressing intra-class variability caused by diverse lighting conditions, shooting environments, and weather factors, particularly when processing images captured at a single exposure level. To enhance the adaptability of these models under complex imaging conditions, this paper proposes a Wavelet-based Exposure Correction method with Degradation Guidance (WEC-DG). Specifically, we introduce a degradation descriptor within the Exposure Consistency Alignment Module (ECAM) at both ends of the processing pipeline to ensure exposure consistency and achieve final alignment. This mechanism effectively addresses miscorrected exposure anomalies caused by existing methods' failure to recognize 'blurred' exposure degradation. Additionally, we investigate the light-detail decoupling properties of the wavelet transform to design the Exposure Restoration and Detail Reconstruction Module (EDRM), which processes low-frequency information related to exposure enhancement before utilizing high-frequency information as a prior guide for reconstructing spatial domain details. This serial processing strategy guarantees precise light correction and enhances detail recovery. Extensive experiments conducted on multiple public datasets demonstrate that the proposed method outperforms existing algorithms, achieving significant performance improvements and validating its effectiveness and practical applicability.