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 876–900 of 983 papers

TitleStatusHype
CAMP-Net: Consistency-Aware Multi-Prior Network for Accelerated MRI ReconstructionCode0
Low-light image enhancement based on sharpening-smoothing image filterCode0
Brightness Perceiving for Recursive Low-Light Image EnhancementCode0
BLNet: A Fast Deep Learning Framework for Low-Light Image Enhancement with Noise Removal and Color RestorationCode0
Low-Light Image and Video Enhancement: A Comprehensive Survey and BeyondCode0
LMT-GP: Combined Latent Mean-Teacher and Gaussian Process for Semi-supervised Low-light Image EnhancementCode0
LLNet: A Deep Autoencoder Approach to Natural Low-light Image EnhancementCode0
The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive VideoCode0
RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image EnhancementCode0
RD-UIE: Relation-Driven State Space Modeling for Underwater Image EnhancementCode0
Dual High-Order Total Variation Model for Underwater Image RestorationCode0
Linear Array Network for Low-light Image EnhancementCode0
LIME: Low-light Image Enhancement via Illumination Map EstimationCode0
Bilateral Interaction for Local-Global Collaborative Perception in Low-Light Image EnhancementCode0
DPFNet: A Dual-branch Dilated Network with Phase-aware Fourier Convolution for Low-light Image EnhancementCode0
Real-world Underwater Enhancement: Challenges, Benchmarks, and SolutionsCode0
Domain Adaptation for Underwater Image EnhancementCode0
Dynamic Test-Time Augmentation via Differentiable FunctionsCode0
Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative DatasetCode0
DLEN: Dual Branch of Transformer for Low-Light Image Enhancement in Dual DomainsCode0
LIME-Eval: Rethinking Low-light Image Enhancement Evaluation via Object DetectionCode0
Reinforcement Learning of Self Enhancing Camera Image and Signal ProcessingCode0
LFW-Beautified: A Dataset of Face Images with Beautification and Augmented Reality FiltersCode0
Reflectance-Oriented Probabilistic Equalization for Image EnhancementCode0
Leveraging Content and Context Cues for Low-Light Image EnhancementCode0
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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