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 851–875 of 983 papers

TitleStatusHype
Medical Image Enhancement Using Histogram Processing and Feature Extraction for Cancer Classification—0
Medical X-Ray Image Enhancement Using Global Contrast-Limited Adaptive Histogram Equalization—0
Method and System for Image Analysis to Detect Cancer—0
MFIF-GAN: A New Generative Adversarial Network for Multi-Focus Image Fusion—0
Microscopic Muscle Image Enhancement—0
MIEHDR CNN: Main Image Enhancement based Ghost-Free High Dynamic Range Imaging using Dual-Lens Systems—0
Modeling Image Tone Dichotomy with the Power Function—0
Modified Alpha-Rooting Color Image Enhancement Method On The Two-Side 2-D Quaternion Discrete Fourier Transform And The 2-D Discrete Fourier Transform—0
Morphological-consistent Diffusion Network for Ultrasound Coronal Image Enhancement—0
Motion-Depth: RGB-D Depth Map Enhancement with Motion and Depth in Complement—0
MSR-net:Low-light Image Enhancement Using Deep Convolutional Network—0
MuLA-GAN: Multi-Level Attention GAN for Enhanced Underwater Visibility—0
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light—0
Multi-Modal Synergistic Implicit Image Enhancement for Efficient Optical Flow Estimation—0
Multiple Latent Space Mapping for Compressed Dark Image Enhancement—0
Image Enhanced Rotation Prediction for Self-Supervised Learning—0
Multi-Scale Structural-aware Exposure Correction for Endoscopic Imaging—0
Multi-Scale Target-Aware Representation Learning for Fundus Image Enhancement—0
Mutual Guidance and Residual Integration for Image Enhancement—0
Mutual-Structure for Joint Filtering—0
MyStyle: A Personalized Generative Prior—0
Natural Color Image Enhancement based on Modified Multiscale Retinex Algorithm and Performance Evaluation usingWavelet Energy—0
Natural Language Supervision for Low-light Image Enhancement—0
Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions—0
New wavelet-based superresolution algorithm for speckle reduction in SAR images—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