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 351–400 of 983 papers

TitleStatusHype
Investigation of the Challenges of Underwater-Visual-Monocular-SLAM—0
Day2Dark: Pseudo-Supervised Activity Recognition beyond Silent Daylight—0
Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement—0
DarkVision: A Benchmark for Low-light Image/Video Perception—0
ARIN: Adaptive Resampling and Instance Normalization for Robust Blind Inpainting of Dunhuang Cave Paintings—0
A Generative Adversarial Approach with Residual Learning for Dust and Scratches Artifacts Removal—0
DA-DRN: Degradation-Aware Deep Retinex Network for Low-Light Image Enhancement—0
A Survey of Fish Tracking Techniques Based on Computer Vision—0
Cycle-Interactive Generative Adversarial Network for Robust Unsupervised Low-Light Enhancement—0
High Accurate Unhealthy Leaf Detection—0
Curved Gabor Filters for Fingerprint Image Enhancement—0
A review of advancements in low-light image enhancement using deep learning—0
A comprehensive benchmark analysis for sand dust image reconstruction—0
A comparative study of paired versus unpaired deep learning methods for physically enhancing digital rock image resolution—0
A Retinex-based Image Enhancement Scheme with Noise Aware Shadow-up Function—0
Guided Collaborative Training for Pixel-wise Semi-Supervised Learning—0
Gray Level Image Enhancement Using Polygonal Functions—0
CuDi: Curve Distillation for Efficient and Controllable Exposure Adjustment—0
IndGIC: Supervised Action Recognition under Low Illumination—0
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement—0
A Retinal Image Enhancement Technique for Blood Vessel Segmentation Algorithm—0
Improving Deep Learning-based Defect Detection on Window Frames with Image Processing Strategies—0
CPDM: Content-Preserving Diffusion Model for Underwater Image Enhancement—0
A Real-Time Framework for Domain-Adaptive Underwater Object Detection with Image Enhancement—0
Improving the perception of visual fiducial markers in the field using Adaptive Active Exposure Control—0
Influence of image noise on crack detection performance of deep convolutional neural networks—0
Information-Theoretic GAN Compression with Variational Energy-based Model—0
Iris Biometric System using a hybrid approach—0
Language Independent Single Document Image Super-Resolution using CNN for improved recognition—0
GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation—0
Convolutional Neural Pyramid for Image Processing—0
Generalized Task-Driven Medical Image Quality Enhancement with Gradient Promotion—0
A Fusion Adversarial Underwater Image Enhancement Network with a Public Test Dataset—0
Convolutional Neural Networks Considering Local and Global features for Image Enhancement—0
Application of Visual Communication in Image Enhancement and Optimization of Human–Computer Interface—0
Controllable Image Enhancement—0
GM-MoE: Low-Light Enhancement with Gated-Mechanism Mixture-of-Experts—0
Cross-Domain Underwater Image Enhancement Guided by No-Reference Image Quality Assessment: A Transfer Learning Approach—0
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model—0
Gradient-Based Low-Light Image Enhancement—0
Image Inpainting by Adaptive Fusion of Variable Spline Interpolations—0
Gray level image enhancement using the Bernstein polynomials—0
Image Restoration in Non-Linear Filtering Domain using MDB approach—0
Guided Colorization Using Mono-Color Image Pairs—0
FusionNet: Multi-model Linear Fusion Framework for Low-light Image Enhancement—0
Contrast Enhancement of Medical X-Ray Image Using Morphological Operators with Optimal Structuring Element—0
CURVE: CLIP-Utilized Reinforcement Learning for Visual Image Enhancement via Simple Image Processing—0
A Retinex based GAN Pipeline to Utilize Paired and Unpaired Datasets for Enhancing Low Light Images—0
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement—0
Contrast Enhancement And Brightness Preservation Using Multi- Decomposition Histogram Equalization—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