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 601–625 of 983 papers

TitleStatusHype
Enhancing Low-Light Images in Real World via Cross-Image Disentanglement—0
Enhanced total variation minimization for stable image reconstruction—0
SGUIE-Net: Semantic Attention Guided Underwater Image Enhancement with Multi-Scale Perception—0
Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety—0
Learning Color Representations for Low-Light Image Enhancement—0
Exposure Normalization and Compensation for Multiple-Exposure Correction—0
GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation—0
Deep Color Consistent Network for Low-Light Image EnhancementCode1
URetinex-Net: Retinex-Based Deep Unfolding Network for Low-Light Image EnhancementCode2
SNR-Aware Low-Light Image EnhancementCode3
Brain Tumor Classification by Cascaded Multiscale Multitask Learning Framework Based on Feature Aggregation—0
Image Edge Restoring Filter—0
Invertible Network for Unpaired Low-light Image Enhancement—0
A Deep-Learning Framework for Improving COVID-19 CT Image Quality and Diagnostic Accuracy—0
A comparative study of paired versus unpaired deep learning methods for physically enhancing digital rock image resolution—0
Image-Adaptive YOLO for Object Detection in Adverse Weather ConditionsCode1
Semantically Contrastive Learning for Low-light Image EnhancementCode1
Attention based Broadly Self-guided Network for Low light Image EnhancementCode0
Learning Deep Context-Sensitive Decomposition for Low-Light Image EnhancementCode1
Image Enhancement via Bilateral Learning—0
Tunable Image Quality Control of 3-D Ultrasound using Switchable CycleGAN—0
A Survey on Deep learning based Document Image Enhancement—0
Seeing Objects in dark with Continual Contrastive Learning—0
Unsupervised Low-Light Image Enhancement via Histogram Equalization PriorCode1
Event Neural NetworksCode0
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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