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 176–200 of 983 papers

TitleStatusHype
Rethinking low-cost microscopy workflow: Image enhancement using deep based Extended Depth of Field methodsCode1
A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film EnhancementCode1
Low-Light Image Enhancement with Multi-Stage Residue Quantization and Brightness-Aware AttentionCode1
Learning a Simple Low-Light Image Enhancer From Paired Low-Light InstancesCode1
DNF: Decouple and Feedback Network for Seeing in the DarkCode1
Adaptive deep learning framework for robust unsupervised underwater image enhancementCode1
Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networksCode1
Semantic-aware Texture-Structure Feature Collaboration for Underwater Image EnhancementCode1
DGD-cGAN: A Dual Generator for Image Dewatering and RestorationCode1
Local Color Distributions Prior for Image EnhancementCode1
Perceptual Multi-Exposure FusionCode1
Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint NetworkCode1
Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog RemovalCode1
PSENet: Progressive Self-Enhancement Network for Unsupervised Extreme-Light Image EnhancementCode1
GDIP: Gated Differentiable Image Processing for Object-Detection in Adverse ConditionsCode1
Reflectance-Guided, Contrast-Accumulated Histogram EqualizationCode1
USLN: A statistically guided lightweight network for underwater image enhancement via dual-statistic white balance and multi-color space stretchCode1
Underwater Ranker: Learn Which Is Better and How to Be BetterCode1
HighlightNet: Highlighting Low-Light Potential Features for Real-Time UAV TrackingCode1
Low-Light Hyperspectral Image EnhancementCode1
Uncertainty Inspired Underwater Image EnhancementCode1
SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image EnhancementCode1
Neural Color Operators for Sequential Image RetouchingCode1
Self-Supervised Low-Light Image Enhancement Using Discrepant Untrained Network PriorsCode1
Structure-consistent Restoration Network for Cataract Fundus Image EnhancementCode1
Show:102550
← PrevPage 8 of 40Next →
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