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
Image enhancement using the mean dynamic range maximization with logarithmic operations—0
Image Enhancement via Bilateral Learning—0
Image Inpainting by Adaptive Fusion of Variable Spline Interpolations—0
Image Restoration in Non-Linear Filtering Domain using MDB approach—0
Importance of Image Enhancement Techniques in Color Image Segmentation: A Comprehensive and Comparative Study—0
Improved Partial Differential Equation and Fast Approximation Algorithm for Hazy/Underwater/Dust Storm Image Enhancement—0
Improved underwater image enhancement algorithms based on partial differential equations (PDEs)—0
Improving Deep Learning-based Defect Detection on Window Frames with Image Processing Strategies—0
Improving the perception of visual fiducial markers in the field using Adaptive Active Exposure Control—0
IndGIC: Supervised Action Recognition under Low Illumination—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
Inhomogeneous illumination image enhancement under ex-tremely low visibility condition—0
Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety—0
Invertible Network for Unpaired Low-light Image Enhancement—0
Investigation of the Challenges of Underwater-Visual-Monocular-SLAM—0
Iris Biometric System using a hybrid approach—0
ISIC 2018-A Method for Lesion Segmentation—0
Iterative Prompt Learning for Unsupervised Backlit Image Enhancement—0
Iterative Thresholded Bi-Histogram Equalization for Medical Image Enhancement—0
ITRE: Low-light Image Enhancement Based on Illumination Transmission Ratio Estimation—0
Joint Image De-noising and Enhancement for Satellite-Based SAR—0
Jointly Adversarial Network to Wavelength Compensation and Dehazing of Underwater Images—0
Joint Perceptual Learning for Enhancement and Object Detection in Underwater Scenarios—0
Joint Regression and Ranking for Image Enhancement—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
3AdaIntPSNR on proRGB25.49—Unverified
4RSFNet-mapPSNR 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