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 376–400 of 983 papers

TitleStatusHype
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
Multiscale Coarse-to-Fine Guided Screenshot DemoiréingCode0
Medium Transmission Map Matters for Learning to Restore Real-World Underwater ImagesCode0
Mamba-UIE: Enhancing Underwater Images with Physical Model ConstraintCode0
Underwater Object Detection Enhancement via Channel StabilizationCode0
MambaUIE&SR: Unraveling the Ocean's Secrets with Only 2.8 GFLOPsCode0
MetaUE: Model-based Meta-learning for Underwater Image EnhancementCode0
Explaining Image Enhancement Black-Box Methods through a Path Planning Based AlgorithmCode0
Exemplar based underwater image enhancement augmented by Wavelet Corrected TransformsCode0
MAC-Lookup: Multi-Axis Conditional Lookup Model for Underwater Image EnhancementCode0
Event Neural NetworksCode0
An Improved Chicken Swarm Optimization Algorithm for Handwritten Document Image EnhancementCode0
An Experimental-based Review of Image Enhancement and Image Restoration Methods for Underwater ImagingCode0
Low-light Stereo Image Enhancement and De-noising in the Low-frequency Information Enhanced Image SpaceCode0
Clearing the Skies: A deep network architecture for single-image rain removalCode0
ERetinex: Event Camera Meets Retinex Theory for Low-Light Image EnhancementCode0
Luminance-Guided Chrominance Image Enhancement for HEVC Intra CodingCode0
Enlighten-Your-Voice: When Multimodal Meets Zero-shot Low-light Image EnhancementCode0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
Enhancing Underwater Imaging with 4-D Light Fields: Dataset and MethodCode0
Low-light image enhancement based on sharpening-smoothing image filterCode0
Low-Light Image and Video Enhancement: A Comprehensive Survey and BeyondCode0
Harnessing Multi-resolution and Multi-scale Attention for Underwater Image RestorationCode0
Low-Light Image Enhancement Based on Cell Vibration Energy Model and Lightness DifferenceCode0
Chest X-ray Image Phase Features for Improved Diagnosis of COVID-19 Using Convolutional Neural NetworkCode0
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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