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 301–325 of 983 papers

TitleStatusHype
Dense residual Transformer for image denoising—0
A Wavelet-based Dual-stream Network for Underwater Image Enhancement—0
A Lightweight Low-Light Image Enhancement Network via Channel Prior and Gamma Correction—0
DEFormer: DCT-driven Enhancement Transformer for Low-light Image and Dark Vision—0
Automatic Spatial Context-Sensitive Cloud/Cloud-Shadow Detection in Multi-Source Multi-Spectral Earth Observation Images: AutoCloud+—0
Deformably-Scaled Transposed Convolution—0
Automated Log-Scale Quantization for Low-Cost Deep Neural Networks—0
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model—0
Deep Symmetric Network for Underexposed Image Enhancement With Recurrent Attentional Learning—0
Learning to Augment: Hallucinating Data for Domain Generalized Segmentation—0
A Correction-Based Dynamic Enhancement Framework towards Underwater Detection—0
GM-MoE: Low-Light Enhancement with Gated-Mechanism Mixture-of-Experts—0
Gradient-Based Low-Light Image Enhancement—0
A Two-stage Unsupervised Approach for Low light Image Enhancement—0
Deep Photo Cropper and Enhancer—0
A hierarchical approach to deep learning and its application to tomographic reconstruction—0
A Poisson-Guided Decomposition Network for Extreme Low-Light Image Enhancement—0
GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation—0
AttentionLut: Attention Fusion-based Canonical Polyadic LUT for Real-time Image Enhancement—0
Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions—0
6D Camera Relocalization in Visually Ambiguous Extreme Environments—0
Deep MR Brain Image Super-Resolution Using Spatio-Structural Priors—0
Generalized Task-Driven Medical Image Quality Enhancement with Gradient Promotion—0
Gray Level Image Enhancement Using Polygonal Functions—0
High Accurate Unhealthy Leaf Detection—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