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 276–300 of 983 papers

TitleStatusHype
Learning A Physical-aware Diffusion Model Based on Transformer for Underwater Image EnhancementCode1
Edge-guided Low-light Image Enhancement with Inertial Bregman Alternating Linearized Minimization—0
A Lightweight Low-Light Image Enhancement Network via Channel Prior and Gamma Correction—0
Misalignment-Robust Frequency Distribution Loss for Image TransformationCode2
ARIN: Adaptive Resampling and Instance Normalization for Robust Blind Inpainting of Dunhuang Cave Paintings—0
Capsule Endoscopy Image Enhancement for Small Intestinal Villi Clarity—0
Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement—0
You Only Need One Color Space: An Efficient Network for Low-light Image EnhancementCode4
Troublemaker Learning for Low-Light Image EnhancementCode1
Visual Text Meets Low-level Vision: A Comprehensive Survey on Visual Text Processing—0
InstructIR: High-Quality Image Restoration Following Human InstructionsCode4
CPDM: Content-Preserving Diffusion Model for Underwater Image Enhancement—0
LYT-NET: Lightweight YUV Transformer-based Network for Low-light Image EnhancementCode2
Edge-Computing-Enabled Deep Learning Approach for Low-Light Satellite Image EnhancementCode0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
PPformer: Using pixel-wise and patch-wise cross-attention for low-light image enhancementCode1
Low-light Stereo Image Enhancement and De-noising in the Low-frequency Information Enhanced Image SpaceCode0
SNeurodCNN: Structure-focused Neurodegeneration Convolutional Neural Network for Modelling and Classification of Alzheimer's DiseaseCode0
Low-light Image Enhancement via CLIP-Fourier Guided Wavelet DiffusionCode2
AttentionLut: Attention Fusion-based Canonical Polyadic LUT for Real-time Image Enhancement—0
Empowering Resampling Operation for Ultra-High-Definition Image Enhancement with Model-Aware GuidanceCode0
Real-Time Exposure Correction via Collaborative Transformations and Adaptive SamplingCode1
USFM: A Universal Ultrasound Foundation Model Generalized to Tasks and Organs towards Label Efficient Image Analysis—0
A Non-Uniform Low-Light Image Enhancement Method with Multi-Scale Attention Transformer and Luminance Consistency LossCode0
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer—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