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 901–925 of 983 papers

TitleStatusHype
Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash—0
Two-stage quality adaptive fingerprint image enhancement using Fuzzy c-means clustering based fingerprint quality analysis—0
Moiré Photo Restoration Using Multiresolution Convolutional Neural NetworksCode0
An Interval Type-2 Fuzzy Approach to Automatic PDF Generation for Histogram Specification—0
Projection image-to-image translation in hybrid X-ray/MR imaging—0
Learning-Based Dequantization For Image Restoration Against Extremely Poor Illumination—0
A Retinal Image Enhancement Technique for Blood Vessel Segmentation Algorithm—0
Predicting Rapid Fire Growth (Flashover) Using Conditional Generative Adversarial Networks—0
Image Enhancement and Noise Reduction Using Modified Delay-Multiply-and-Sum Beamformer: Application to Medical Photoacoustic Imaging—0
A PDE-based log-agnostic illumination correction algorithm—0
Sky detection and log illumination refinement for PDE-based hazy image contrast enhancement—0
Deep Burst DenoisingCode0
On the Duality Between Retinex and Image Dehazing—0
Learned Perceptual Image Enhancement—0
Taming Adversarial Domain Transfer with Structural Constraints for Image Enhancement—0
Properties on n-dimensional convolution for image deconvolution—0
Learning Aggregated Transmission Propagation Networks for Haze Removal and Beyond—0
MSR-net:Low-light Image Enhancement Using Deep Convolutional Network—0
A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement—0
Classification Driven Dynamic Image Enhancement—0
Importance of Image Enhancement Techniques in Color Image Segmentation: A Comprehensive and Comparative Study—0
Fingerprint Extraction Using Smartphone Camera—0
Aesthetic-Driven Image Enhancement by Adversarial LearningCode0
Modified Alpha-Rooting Color Image Enhancement Method On The Two-Side 2-D Quaternion Discrete Fourier Transform And The 2-D Discrete Fourier Transform—0
Deep Bilateral Learning for Real-Time Image EnhancementCode0
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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