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 151–175 of 983 papers

TitleStatusHype
Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image EnhancementCode1
CCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image BinarizationCode1
CDAN: Convolutional dense attention-guided network for low-light image enhancementCode1
Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-rays ImagesCode1
A New Benchmark In Vivo Paired Dataset for Laparoscopic Image De-smokingCode1
ExposureDiffusion: Learning to Expose for Low-light Image EnhancementCode1
DMFourLLIE: Dual-Stage and Multi-Branch Fourier Network for Low-Light Image EnhancementCode1
FDCE-Net: Underwater Image Enhancement with Embedding Frequency and Dual Color EncoderCode1
DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-ResolutionCode1
CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image GenerationCode1
DNF: Decouple and Feedback Network for Seeing in the DarkCode1
DPF-Net: Physical Imaging Model Embedded Data-Driven Underwater Image EnhancementCode1
DGD-cGAN: A Dual Generator for Image Dewatering and RestorationCode1
Fundus image enhancement through direct diffusion bridgesCode1
GDIP: Gated Differentiable Image Processing for Object-Detection in Adverse ConditionsCode1
Generalized Lightness Adaptation with Channel Selective NormalizationCode1
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and LatencyCode1
Glow in the Dark: Low-Light Image Enhancement with External MemoryCode1
Harmonizing Pathological and Normal Pixels for Pseudo-healthy SynthesisCode1
High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented TransformerCode1
Diff-Mosaic: Augmenting Realistic Representations in Infrared Small Target Detection via Diffusion PriorCode1
Human Guided Ground-truth Generation for Realistic Image Super-resolutionCode1
Degrade is Upgrade: Learning Degradation for Low-light Image EnhancementCode1
Boosting Object Detection with Zero-Shot Day-Night Domain AdaptationCode1
Denoising Diffusion Post-Processing for Low-Light Image EnhancementCode1
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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