DLFE-Net: Preserving Details and Removing Noise Using HVI Color Space for Low-Light Image Enhancement

This paper proposes a novel Denoiser and Low-Frequency Enhancer Network (DLFE-Net) for Low-Light Image Enhancement (LLIE). The DLFE-Net addresses two key challenges: (1) overexposure and detail loss in local areas during enhancement, and (2) the effective removal of inherent noise in low-light images. Specifically, the input RGB image is first converted to the HVI color space. The intensity (I) and color (H, V) maps are then enhanced and denoised separately, i.e., preserving details and removing noise. For preserving details, the Low-Frequency Illumination Enhancer (LFIE) module isolates and processes the image's low-frequency information. This targeted approach effectively mitigates local overexposure and preserves fine details during enhancement. For removing noise, the Multi-Scale Gated Denoiser (MSGD) module performs denoising through strong preservation after predicting image noise. Comprehensive experiments were conducted on three benchmark datasets (LOL, SICE, Sony-Total-Dark) and five unpaired datasets. Both qualitative and quantitative analyses demonstrated the superiority of DLFE-Net over state-of-the-art methods. Moreover, ablation studies demonstrated the effectiveness of each module in DLFE-Net.

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Publication Details

Journal
Sensors
Published
2025-08-29
DOI
https://doi.org/10.3390/s25175353
Citations
1
Primary Topic
Image Enhancement Techniques
Type
article
Field-Weighted Citation Impact
1.28

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article

DLFE-Net: Preserving Details and Removing Noise Using HVI Color Space for Low-Light Image Enhancement

Guozhu Hao, Wei Wang, Xin Yuan, Zhaokun He
1 citations
Sensors
Image Enhancement Techniques
1.28
article

DLFE-Net: Preserving Details and Removing Noise Using HVI Color Space for Low-Light Image Enhancement

Guozhu Hao, Wei Wang, Xin Yuan, Zhaokun He
article en
1 citations

Abstract

This paper proposes a novel Denoiser and Low-Frequency Enhancer Network (DLFE-Net) for Low-Light Image Enhancement (LLIE). The DLFE-Net addresses two key challenges: (1) overexposure and detail loss in local areas during enhancement, and (2) the effective removal of inherent noise in low-light images. Specifically, the input RGB image is first converted to the HVI color space. The intensity (I) and color (H, V) maps are then enhanced and denoised separately, i.e., preserving details and removing noise. For preserving details, the Low-Frequency Illumination Enhancer (LFIE) module isolates and processes the image's low-frequency information. This targeted approach effectively mitigates local overexposure and preserves fine details during enhancement. For removing noise, the Multi-Scale Gated Denoiser (MSGD) module performs denoising through strong preservation after predicting image noise. Comprehensive experiments were conducted on three benchmark datasets (LOL, SICE, Sony-Total-Dark) and five unpaired datasets. Both qualitative and quantitative analyses demonstrated the superiority of DLFE-Net over state-of-the-art methods. Moreover, ablation studies demonstrated the effectiveness of each module in DLFE-Net.

SensorsVol. 25(17)
Wuhan University of Technology (CN), China Ocean Shipping (China) (CN), Wuhan University of Science and Technology (CN)
Strong
Openalex Percentile: Top 16%
Image Enhancement Techniques
1.28
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DLFE-Net: Preserving Details and Removing Noise Using HVI Color Space for Low-Light Image Enhancement — Guozhu Hao, Wei Wang, et al. · Sensors (2025) | TGRS Research Map | TGRS