SOTAVerified

Image Enhancement

Image Enhancement is basically improving the interpretability or perception of information in images for human viewers and providing ‘better’ input for other automated image processing techniques. The principal objective of Image Enhancement is to modify attributes of an image to make it more suitable for a given task and a specific observer.

Source: A Comprehensive Review of Image Enhancement Techniques

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 983 papers

TitleStatusHype
LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image EnhancementCode1
Adversarial Color Enhancement: Generating Unrestricted Adversarial Images by Optimizing a Color FilterCode1
Domain Adaptation for Underwater Image Enhancement via Content and Style SeparationCode1
HUPE: Heuristic Underwater Perceptual Enhancement with Semantic Collaborative LearningCode1
Improving Underwater Visual Tracking With a Large Scale Dataset and Image EnhancementCode1
Deep Photo Scan: Semi-Supervised Learning for dealing with the real-world degradation in Smartphone Photo ScanningCode1
A New Benchmark In Vivo Paired Dataset for Laparoscopic Image De-smokingCode1
Global Structure-Aware Diffusion Process for Low-Light Image EnhancementCode1
Getting to Know Low-light Images with The Exclusively Dark DatasetCode1
Generalized Lightness Adaptation with Channel Selective NormalizationCode1
Glow in the Dark: Low-Light Image Enhancement with External MemoryCode1
Fundus image enhancement through direct diffusion bridgesCode1
From Generation to Suppression: Towards Effective Irregular Glow Removal for Nighttime Visibility EnhancementCode1
GDB: Gated convolutions-based Document BinarizationCode1
Burst Photography for Learning to Enhance Extremely Dark ImagesCode1
DeepLPF: Deep Local Parametric Filters for Image EnhancementCode1
Burst Image Restoration and EnhancementCode1
Burst Denoising of Dark ImagesCode1
Adaptive deep learning framework for robust unsupervised underwater image enhancementCode1
FourLLIE: Boosting Low-Light Image Enhancement by Fourier Frequency InformationCode1
Burst Super-Resolution with Diffusion Models for Improving Perceptual QualityCode1
Adaptive Unfolding Total Variation Network for Low-Light Image EnhancementCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
Deep Color Consistent Network for Low-Light Image EnhancementCode1
GDIP: Gated Differentiable Image Processing for Object-Detection in Adverse ConditionsCode1
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All datasetsMIT-Adobe 5kTIP 2018Exposure-ErrorsMIT-Adobe FiveKSICE-GradSICE-Mix

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HG-MTFEPSNR on proRGB25.69—Unverified
2PQDynamicISPPSNR on proRGB25.53—Unverified
3RSFNet-mapPSNR on proRGB25.49—Unverified
4AdaIntPSNR on proRGB25.49—Unverified
5SepLUTPSNR on proRGB25.47—Unverified
6MTFEPSNR on proRGB25.46—Unverified
73D LUTPSNR on proRGB25.21—Unverified
8RetinexformerPSNR on sRGB24.94—Unverified
94D LUTPSNR on proRGB24.61—Unverified
10DIFAR (MSCA, level 1)PSNR on proRGB24.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR30.11—Unverified
2MBCNNPSNR30.03—Unverified
3ESDNetPSNR29.81—Unverified
4Uformer-BPSNR29.28—Unverified
5MopNetPSNR27.75—Unverified
6DMCNNPSNR26.77—Unverified
#ModelMetricClaimedVerifiedStatus
1Exposure-slotPSNR23.18—Unverified
2CSECPSNR22.73—Unverified
3LCDPNetPSNR22.17—Unverified
4IATPSNR20.34—Unverified
5MSECPSNR20.21—Unverified
#ModelMetricClaimedVerifiedStatus
1TreEnhanceDeltaE11.25—Unverified
#ModelMetricClaimedVerifiedStatus
1CIDNetAverage PSNR13.45—Unverified
#ModelMetricClaimedVerifiedStatus
1CIDNetAverage PSNR13.43—Unverified