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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 551–560 of 983 papers

Title	Date	Tasks	Status
Fast Enhancement for Non-Uniform Illumination Images using Light-weight CNNs	May 31, 2020	Image Enhancement	—Unverified
Feature Attention Network (FA-Net): A Deep-Learning Based Approach for Underwater Single Image Enhancement	Aug 30, 2023	Image Enhancement	—Unverified
Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentation	Sep 7, 2023	DecoderImage Enhancement	—Unverified
Feedback Graph Attention Convolutional Network for Medical Image Enhancement	Jun 24, 2020	Diffusion MRIGraph Attention	—Unverified
FGF-GAN: A Lightweight Generative Adversarial Network for Pansharpening via Fast Guided Filter	Dec 31, 2020	Generative Adversarial NetworkImage Enhancement	—Unverified
Fingerprint Extraction Using Smartphone Camera	Aug 2, 2017	fingerprint verificationImage Enhancement	—Unverified
Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network	May 13, 2020	Image Enhancement	—Unverified
Forensic Video Analytic Software	Sep 17, 2023	Activity RecognitionAnomaly Detection	—Unverified
Fractional Calculus In Image Processing: A Review	Aug 10, 2016	DenoisingEdge Detection	—Unverified
1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition	Jul 2, 2021	Face DetectionImage Enhancement	—Unverified

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All datasets MIT-Adobe 5k TIP 2018 Exposure-Errors MIT-Adobe FiveK SICE-Grad SICE-Mix

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	HG-MTFE	PSNR on proRGB	25.69	—	Unverified
2	PQDynamicISP	PSNR on proRGB	25.53	—	Unverified
3	RSFNet-map	PSNR on proRGB	25.49	—	Unverified
4	AdaInt	PSNR on proRGB	25.49	—	Unverified
5	SepLUT	PSNR on proRGB	25.47	—	Unverified
6	MTFE	PSNR on proRGB	25.46	—	Unverified
7	3D LUT	PSNR on proRGB	25.21	—	Unverified
8	Retinexformer	PSNR on sRGB	24.94	—	Unverified
9	4D LUT	PSNR on proRGB	24.61	—	Unverified
10	DIFAR (MSCA, level 1)	PSNR on proRGB	24.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ESDNet-L	PSNR	30.11	—	Unverified
2	MBCNN	PSNR	30.03	—	Unverified
3	ESDNet	PSNR	29.81	—	Unverified
4	Uformer-B	PSNR	29.28	—	Unverified
5	MopNet	PSNR	27.75	—	Unverified
6	DMCNN	PSNR	26.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Exposure-slot	PSNR	23.18	—	Unverified
2	CSEC	PSNR	22.73	—	Unverified
3	LCDPNet	PSNR	22.17	—	Unverified
4	IAT	PSNR	20.34	—	Unverified
5	MSEC	PSNR	20.21	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TreEnhance	DeltaE	11.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CIDNet	Average PSNR	13.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CIDNet	Average PSNR	13.43	—	Unverified