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 126–150 of 983 papers

TitleStatusHype
An Improved Chicken Swarm Optimization Algorithm for Handwritten Document Image EnhancementCode0
Efficient Diffusion as Low Light Enhancer—0
Bayesian Enhancement Models for One-to-Many Mapping in Image EnhancementCode2
LoLI-Street: Benchmarking Low-Light Image Enhancement and BeyondCode1
LIME-Eval: Rethinking Low-light Image Enhancement Evaluation via Object DetectionCode0
Image Enhancement Based on Histogram-Guided Multiple Transformation Function EstimationCode0
Generalizability analysis of deep learning predictions of human brain responses to augmented and semantically novel visual stimuliCode0
A New Benchmark In Vivo Paired Dataset for Laparoscopic Image De-smokingCode1
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
GMT: Enhancing Generalizable Neural Rendering via Geometry-Driven Multi-Reference Texture TransferCode0
Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and InterpolationCode2
PDCFNet: Enhancing Underwater Images through Pixel Difference ConvolutionCode0
Underwater Image Enhancement with Physical-based Denoising Diffusion Implicit ModelsCode1
Unsupervised Low-light Image Enhancement with Lookup Tables and Diffusion Priors—0
SinoSynth: A Physics-based Domain Randomization Approach for Generalizable CBCT Image EnhancementCode0
Morphological-consistent Diffusion Network for Ultrasound Coronal Image Enhancement—0
Semi-LLIE: Semi-supervised Contrastive Learning with Mamba-based Low-light Image EnhancementCode1
UICE-MIRNet guided image enhancement for underwater object detection—0
For Overall Nighttime Visibility: Integrate Irregular Glow Removal With Glow-Aware EnhancementCode1
Quantitative and Qualitative Evaluation of NLM and Wavelet Methods in Image Enhancement—0
Low-Light Enhancement Effect on Classification and Detection: An Empirical Study—0
Fundus image enhancement through direct diffusion bridgesCode1
CUNSB-RFIE: Context-aware Unpaired Neural Schr"odinger Bridge in Retinal Fundus Image EnhancementCode1
Ultrasound Image Enhancement with the Variance of Diffusion ModelsCode1
Underwater Image Enhancement via Dehazing and Color Restoration—0
Show:102550
← PrevPage 6 of 40Next →
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