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 51–75 of 983 papers

TitleStatusHype
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule EndoscopyCode1
Enhance Images as You Like with Unpaired LearningCode1
A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film EnhancementCode1
Effective Document Image Enhancement Using tokens-to-token Transformer NetworkCode1
DPF-Net: Physical Imaging Model Embedded Data-Driven Underwater Image EnhancementCode1
A guided edge-aware smoothing-sharpening filter based on patch interpolation model and generalized Gamma distributionCode1
A Layer-Wise Tokens-to-Token Transformer Network for Improved Historical Document Image EnhancementCode1
Early Exit or Not: Resource-Efficient Blind Quality Enhancement for Compressed ImagesCode1
7T MRI Synthesization from 3T AcquisitionsCode1
Empowering Low-Light Image Enhancer through Customized Learnable PriorsCode1
End-To-End Underwater Video Enhancement: Dataset and ModelCode1
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image EnhancementCode1
DNF: Decouple and Feedback Network for Seeing in the DarkCode1
DMFourLLIE: Dual-Stage and Multi-Branch Fourier Network for Low-Light Image EnhancementCode1
DocEnTr: An End-to-End Document Image Enhancement TransformerCode1
A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation LearningCode1
3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical ImagesCode1
DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-ResolutionCode1
Domain Adaptation for Underwater Image Enhancement via Content and Style SeparationCode1
DGD-cGAN: A Dual Generator for Image Dewatering and RestorationCode1
A Generalized Physical-knowledge-guided Dynamic Model for Underwater Image EnhancementCode1
Diff-Mosaic: Augmenting Realistic Representations in Infrared Small Target Detection via Diffusion PriorCode1
A Gated Cross-domain Collaborative Network for Underwater Object DetectionCode1
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and LatencyCode1
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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