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 201–225 of 983 papers

TitleStatusHype
NILUT: Conditional Neural Implicit 3D Lookup Tables for Image EnhancementCode1
DALE : Dark Region-Aware Low-light Image EnhancementCode1
Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image EnhancementCode1
FDCE-Net: Underwater Image Enhancement with Embedding Frequency and Dual Color EncoderCode1
OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by EnhancingCode1
Effective Document Image Enhancement Using tokens-to-token Transformer NetworkCode1
Early Exit or Not: Resource-Efficient Blind Quality Enhancement for Compressed ImagesCode1
Gap-closing Matters: Perceptual Quality Evaluation and Optimization of Low-Light Image EnhancementCode1
PixMamba: Leveraging State Space Models in a Dual-Level Architecture for Underwater Image EnhancementCode1
Poisson2Sparse: Self-Supervised Poisson Denoising From a Single ImageCode1
A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation LearningCode1
Decoupled Low-light Image EnhancementCode1
PromptCIR: Blind Compressed Image Restoration with Prompt LearningCode1
Prompt-Guided Image-Adaptive Neural Implicit Lookup Tables for Interpretable Image EnhancementCode1
Diff-Mosaic: Augmenting Realistic Representations in Infrared Small Target Detection via Diffusion PriorCode1
RAUNE-Net: A Residual and Attention-Driven Underwater Image Enhancement MethodCode1
Deep Color Consistent Network for Low-Light Image EnhancementCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
Real-Time Exposure Correction via Collaborative Transformations and Adaptive SamplingCode1
Recurrent Exposure Generation for Low-Light Face DetectionCode1
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the DarkCode1
Reinforced Swin-Convs Transformer for Underwater Image EnhancementCode1
DeepLPF: Deep Local Parametric Filters for Image EnhancementCode1
A guided edge-aware smoothing-sharpening filter based on patch interpolation model and generalized Gamma distributionCode1
Empowering Low-Light Image Enhancer through Customized Learnable PriorsCode1
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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