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 801–850 of 983 papers

TitleStatusHype
K-means segmentation based-on lab color space for embryo detection in incubated egg—0
L2BGAN: An image enhancement model for image quality improvement and image analysis tasks without paired supervision—0
LAFFNet: A Lightweight Adaptive Feature Fusion Network for Underwater Image Enhancement—0
Language Independent Single Document Image Super-Resolution using CNN for improved recognition—0
Latent Disentanglement for Low Light Image Enhancement—0
Learned Perceptual Image Enhancement—0
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer—0
Learning Aggregated Transmission Propagation Networks for Haze Removal and Beyond—0
1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition—0
Learning a Single Convolutional Layer Model for Low Light Image Enhancement—0
Learning-Based Dequantization For Image Restoration Against Extremely Poor Illumination—0
Learning-based Image Enhancement for Visual Odometry in Challenging HDR Environments—0
Learning Color Representations for Low-Light Image Enhancement—0
Learning Dynamic Guidance for Depth Image Enhancement—0
Learning Enriched Features for Fast Image Restoration and Enhancement—0
Learning Physics-Informed Color-Aware Transforms for Low-Light Image Enhancement—0
Learning to Adapt to Light—0
Learning to Harmonize Cross-vendor X-ray Images by Non-linear Image Dynamics Correction—0
Learning to Restore Low-Light Images via Decomposition-and-Enhancement—0
Learning to See Low-Light Images via Feature Domain Adaptation—0
Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions—0
LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset—0
LEUGAN:Low-Light Image Enhancement by Unsupervised Generative Attentional Networks—0
Lightening Anything in Medical Images—0
Lightweight HDR Camera ISP for Robust Perception in Dynamic Illumination Conditions via Fourier Adversarial Networks—0
Lightweight Image Enhancement Network for Mobile Devices Using Self-Feature Extraction and Dense Modulation—0
LIME: A Method for Low-light IMage Enhancement—0
Liver Segmentation from Multimodal Images using HED-Mask R-CNN—0
LLGS: Unsupervised Gaussian Splatting for Image Enhancement and Reconstruction in Pure Dark Environment—0
Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data—0
LoLi-IEA: low-light image enhancement algorithm—0
Low-Dose CT Image Enhancement Using Deep Learning—0
Enhanced Low-Dose CT Image Reconstruction by Domain and Task Shifting Gaussian Denoisers—0
Low-Light Enhancement Effect on Classification and Detection: An Empirical Study—0
Low-Light Enhancement in the Frequency Domain—0
Low-light Enhancement Method Based on Attention Map Net—0
Low-light Image Enhancement Algorithm Based on Retinex and Generative Adversarial Network—0
Low-Light Image Enhancement by Learning Contrastive Representations in Spatial and Frequency Domains—0
Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment—0
Low-Light Image Enhancement using Event-Based Illumination Estimation—0
Low Light Image Enhancement via Global and Local Context Modeling—0
Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Network—0
Low-Light Video Enhancement with Synthetic Event Guidance—0
LU2Net: A Lightweight Network for Real-time Underwater Image Enhancement—0
LUMINA-Net: Low-light Upgrade through Multi-stage Illumination and Noise Adaptation Network for Image Enhancement—0
Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision—0
LUT-GCE: Lookup Table Global Curve Estimation for Fast Low-light Image Enhancement—0
MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space—0
MambaTrack: Exploiting Dual-Enhancement for Night UAV Tracking—0
Mammographic Image Enhancement using Digital Image Processing Technique—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
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