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
Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image EnhancementCode1
Learning Multi-Scale Photo Exposure CorrectionCode1
Low-Light Maritime Image Enhancement with Regularized Illumination Optimization and Deep Noise SuppressionCode1
Simplifying Low-Light Image Enhancement Networks with Relative Loss FunctionsCode1
Conditional Consistency Guided Image Translation and EnhancementCode1
Learning A Physical-aware Diffusion Model Based on Transformer for Underwater Image EnhancementCode1
Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-rays ImagesCode1
Learning an Adaptive Model for Extreme Low-light Raw Image ProcessingCode1
Learning a Simple Low-Light Image Enhancer From Paired Low-Light InstancesCode1
ExposureDiffusion: Learning to Expose for Low-light Image EnhancementCode1
Exposure-slot: Exposure-centric representations learning with Slot-in-Slot Attention for Region-aware Exposure CorrectionCode1
Deep Photo Scan: Semi-Supervised Learning for dealing with the real-world degradation in Smartphone Photo ScanningCode1
Learn from Unpaired Data for Image Restoration: A Variational Bayes ApproachCode1
NILUT: Conditional Neural Implicit 3D Lookup Tables for Image EnhancementCode1
Learning Deep Context-Sensitive Decomposition for Low-Light Image EnhancementCode1
Joint Correcting and Refinement for Balanced Low-Light Image EnhancementCode1
DeepLPF: Deep Local Parametric Filters for Image EnhancementCode1
Joint RGB-Spectral Decomposition Model Guided Image Enhancement in Mobile PhotographyCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
Boosting Object Detection with Zero-Shot Day-Night Domain AdaptationCode1
CUNSB-RFIE: Context-aware Unpaired Neural Schr"odinger Bridge in Retinal Fundus Image EnhancementCode1
FourLLIE: Boosting Low-Light Image Enhancement by Fourier Frequency InformationCode1
For Overall Nighttime Visibility: Integrate Irregular Glow Removal With Glow-Aware EnhancementCode1
Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint NetworkCode1
KAN See In the DarkCode1
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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