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 326–350 of 983 papers

TitleStatusHype
Perceptual Variousness Motion Deblurring With Light Global Context RefinementCode0
Personalized Image Enhancement Featuring Masked Style ModelingCode0
Low-light Image Enhancement Using the Cell Vibration ModelCode0
PDCFNet: Enhancing Underwater Images through Pixel Difference ConvolutionCode0
CUR Transformer: A Convolutional Unbiased Regional Transformer for Image DenoisingCode0
A GAN-Enhanced Deep Learning Framework for Rooftop Detection from Historical Aerial ImageryCode0
Advancing Unsupervised Low-light Image Enhancement: Noise Estimation, Illumination Interpolation, and Self-RegulationCode0
A Practical Framework for Unsupervised Structure Preservation Medical Image EnhancementCode0
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
Mop Moire Patterns Using MopNetCode0
Multi-image Tranformer for Multi-focus Image FusionCode0
MetaUE: Model-based Meta-learning for Underwater Image EnhancementCode0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
Context-Aware Optimal Transport Learning for Retinal Fundus Image EnhancementCode0
A Physical Model-Guided Framework for Underwater Image Enhancement and Depth EstimationCode0
Moiré Photo Restoration Using Multiresolution Convolutional Neural NetworksCode0
Context-Aware Automatic Occlusion RemovalCode0
Mamba-UIE: Enhancing Underwater Images with Physical Model ConstraintCode0
MambaUIE&SR: Unraveling the Ocean's Secrets with Only 2.8 GFLOPsCode0
Luminance-Guided Chrominance Image Enhancement for HEVC Intra CodingCode0
An Underwater Image Enhancement Benchmark Dataset and BeyondCode0
Aesthetic-Driven Image Enhancement by Adversarial LearningCode0
Low-light Stereo Image Enhancement and De-noising in the Low-frequency Information Enhanced Image SpaceCode0
MAC-Lookup: Multi-Axis Conditional Lookup Model for Underwater Image EnhancementCode0
Medium Transmission Map Matters for Learning to Restore Real-World Underwater ImagesCode0
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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
3AdaIntPSNR on proRGB25.49—Unverified
4RSFNet-mapPSNR 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