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 451–475 of 983 papers

TitleStatusHype
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
AttentionLut: Attention Fusion-based Canonical Polyadic LUT for Real-time Image Enhancement—0
Improving the perception of visual fiducial markers in the field using Adaptive Active Exposure Control—0
When No-Reference Image Quality Models Meet MAP Estimation in Diffusion Latents—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
3D Conditional Generative Adversarial Networks to enable large-scale seismic image enhancement—0
Feedback Graph Attention Convolutional Network for Medical Image Enhancement—0
Comparative Analysis of Image Enhancement Techniques for Brain Tumor Segmentation: Contrast, Histogram, and Hybrid Approaches—0
Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentation—0
Feature Attention Network (FA-Net): A Deep-Learning Based Approach for Underwater Single Image Enhancement—0
ISIC 2018-A Method for Lesion Segmentation—0
Comparative analysis of evolutionary algorithms for image enhancement—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
A Novel Underwater Image Enhancement and Improved Underwater Biological Detection Pipeline—0
LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset—0
Color-wise Attention Network for Low-light Image Enhancement—0
Deformably-Scaled Transposed Convolution—0
Fast Enhancement for Non-Uniform Illumination Images using Light-weight CNNs—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