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 776–800 of 983 papers

TitleStatusHype
Learning to Restore Low-Light Images via Decomposition-and-Enhancement—0
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement—0
Fast Enhancement for Non-Uniform Illumination Images using Light-weight CNNs—0
Positron Emission Tomography (PET) image enhancement using a gradient vector orientation based nonlinear diffusion filter (GVOF) for accurate quantitation of radioactivity concentration—0
Attention-based network for low-light image enhancement—0
Color-wise Attention Network for Low-light Image Enhancement—0
Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement—0
Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network—0
Modeling and Enhancing Low-quality Retinal Fundus ImagesCode1
Encoding in the Dark Grand Challenge: An Overview—0
Unsupervised Low-light Image Enhancement with Decoupled Networks—0
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and LatencyCode1
Learning an Adaptive Model for Extreme Low-light Raw Image ProcessingCode1
Reconstruction of high-resolution 6x6-mm OCT angiograms using deep learning—0
Superkernel Neural Architecture Search for Image Denoising—0
Underwater image enhancement with Image Colorfulness Measure—0
On Box-Cox Transformation for Image Normality and Pattern Classification—0
Underwater Image Enhancement Based on Structure-Texture Reconstruction—0
Harmony-Search and Otsu based System for Coronavirus Disease (COVID-19) Detection using Lung CT Scan ImagesCode0
Image Demoireing with Learnable Bandpass FiltersCode1
DeepLPF: Deep Local Parametric Filters for Image EnhancementCode1
Super Resolution for Root ImagingCode0
Polarized Reflection Removal with Perfect Alignment in the WildCode1
Learning Multi-Scale Photo Exposure CorrectionCode1
Pre-processing Image using Brightening, CLAHE and RETINEXCode1
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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