2025 · 28 citations · 38 references
ArtsBiomedical EngineeringComputer ScienceComputer VisionDigital ImagingMachine LearningDigital Image ProcessingDigital Signal ProcessingImage EnhancementImage ProcessingImage QualityImage RestorationAdditive NoiseDenoisingImage DenoisingImage Noise ReductionObjective EvaluationState-of-the-art Review
This paper presents an overview of the NTIRE 2025 Image Denoising Challenge (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\sigma=50$</tex>), highlighting the proposed methodologies and corresponding results. The primary objective is to develop a network architecture capable of achieving high-quality denoising performance, quantitatively evaluated using PSNR, without constraints on computational complexity or model size. The task assumes independent additive white Gaussian noise (AWGN) with a fixed noise level of 50. A total of 290 participants registered for the challenge, with 20 teams successfully submitting valid results, providing insights into the current state-of-the-art in image denoising.
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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
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scikit-image: image processing in Python
Stéfan van der Walt, Johannes L. Schönberger, Juan Nunez-Iglesias et al. · PeerJ · 2014 · 6.9K citations · Full text
SwinIR: Image Restoration Using Swin Transformer
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Edwin H. Land, John J. McCann · Journal of the Optical Society of America · 1971 · 4K citations
Medicine, Physiology, Vision Science +14