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
Zero-Shot Enhancement of Low-Light Image Based on Retinex DecompositionCode0
RAUNE-Net: A Residual and Attention-Driven Underwater Image Enhancement MethodCode1
UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale TransformerCode0
Low-Dose CT Image Enhancement Using Deep Learning—0
Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone MappingCode1
Global Structure-Aware Diffusion Process for Low-Light Image EnhancementCode1
Unifying Image Processing as Visual Prompting Question Answering—0
Dimma: Semi-supervised Low Light Image Enhancement with Adaptive DimmingCode1
WaveNet: Wave-Aware Image EnhancementCode1
ITRE: Low-light Image Enhancement Based on Illumination Transmission Ratio Estimation—0
Towards A Robust Group-level Emotion Recognition via Uncertainty-Aware Learning—0
LoLi-IEA: low-light image enhancement algorithm—0
CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image GenerationCode1
Exchange means change: an unsupervised single-temporal change detection framework based on intra- and inter-image patch exchangeCode1
Joint Correcting and Refinement for Balanced Low-Light Image EnhancementCode1
Bootstrap Diffusion Model Curve Estimation for High Resolution Low-Light Image Enhancement—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
Multimodal Transformers for Wireless Communications: A Case Study in Beam PredictionCode1
Multi-image Tranformer for Multi-focus Image FusionCode0
Forensic Video Analytic Software—0
AOSR-Net: All-in-One Sandstorm Removal Network—0
Dual-Camera Joint Deblurring-Denoising—0
Double Domain Guided Real-Time Low-Light Image Enhancement for Ultra-High-Definition Transportation SurveillanceCode1
Improving Deep Learning-based Defect Detection on Window Frames with Image Processing Strategies—0
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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