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 476–500 of 983 papers

TitleStatusHype
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
Visual Text Meets Low-level Vision: A Comprehensive Survey on Visual Text Processing—0
CPDM: Content-Preserving Diffusion Model for Underwater Image Enhancement—0
Edge-Computing-Enabled Deep Learning Approach for Low-Light Satellite Image EnhancementCode0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
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
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
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
MuLA-GAN: Multi-Level Attention GAN for Enhanced Underwater Visibility—0
Revealing Shadows: Low-Light Image Enhancement Using Self-Calibrated Illumination—0
JoReS-Diff: Joint Retinex and Semantic Priors in Diffusion Model for Low-light Image Enhancement—0
Texture Matching GAN for CT Image Enhancement—0
ClassLIE: Structure- and Illumination-Adaptive Classification for Low-Light Image Enhancement—0
Ultrasound Image Enhancement using CycleGAN and Perceptual LossCode0
A Case Study of Image Enhancement Algorithms' Effectiveness of Improving Neural Networks' Performance on Adverse Images—0
Enlighten-Your-Voice: When Multimodal Meets Zero-shot Low-light Image EnhancementCode0
System Integration of Xilinx DPU and HDMI for Real-Time inference in PYNQ Environment with Image Enhancement—0
DiffuseRAW: End-to-End Generative RAW Image Processing for Low-Light Images—0
DGNet: Dynamic Gradient-Guided Network for Water-Related Optics Image Enhancement—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