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 626–650 of 983 papers

TitleStatusHype
4D LUT: Learnable Context-Aware 4D Lookup Table for Image Enhancement—0
2nd Place Solutions for UG2+ Challenge 2022 -- D^3Net for Mitigating Atmospheric Turbulence from Images—0
Low-Light Video Enhancement with Synthetic Event Guidance—0
An End-to-End OCR Framework for Robust Arabic-Handwriting Recognition using a Novel Transformers-based Model and an Innovative 270 Million-Words Multi-Font Corpus of Classical Arabic with Diacritics—0
Low-light Enhancement Method Based on Attention Map Net—0
Local Low-light Image Enhancement via Region-Aware Normalization—0
Learning Hierarchical Dynamics with Spatial Adjacency for Image EnhancementCode0
Underwater enhancement based on a self-learning strategy and attention mechanism for high-intensity regions—0
CuDi: Curve Distillation for Efficient and Controllable Exposure Adjustment—0
Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement—0
Enhancement by Your Aesthetic: An Intelligible Unsupervised Personalized Enhancer for Low-Light Images—0
Explaining Image Enhancement Black-Box Methods through a Path Planning Based AlgorithmCode0
6D Camera Relocalization in Visually Ambiguous Extreme Environments—0
On the limits of perceptual quality measures for enhanced underwater images—0
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model—0
A Novel Hybrid Endoscopic Dataset for Evaluating Machine Learning-based Photometric Image Enhancement Models—0
Cycle-Interactive Generative Adversarial Network for Robust Unsupervised Low-Light Enhancement—0
Face Image Lighting Enhancement Using a 3D Model—0
A novel approach for glaucoma classification by wavelet neural networks using graph-based, statisitcal features of qualitatively improved images—0
Controllable Image Enhancement—0
Luminance-Guided Chrominance Image Enhancement for HEVC Intra CodingCode0
A Novel Underwater Image Enhancement and Improved Underwater Biological Detection Pipeline—0
UIF: An Objective Quality Assessment for Underwater Image Enhancement—0
Towards Robust Low Light Image Enhancement—0
Dense residual Transformer for image denoising—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