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Adversarial Gaussian Denoiser for Multiple-Level Image Denoising [PDF]
Sensors, 2021 Image denoising is a challenging task that is essential in numerous computer vision and image processing problems. This study proposes and applies a generative adversarial network-based image denoising training architecture to multiple-level Gaussian ...
Aamir Khan +4 more
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Medical image denoising using convolutional denoising autoencoders [PDF]
2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 2016 Image denoising is an important pre-processing step in medical image analysis. Different algorithms have been proposed in past three decades with varying denoising performances.
Gondara, Lovedeep
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Boosting of Image Denoising Algorithms [PDF]
SIAM Journal on Imaging Sciences, 2015 In this paper we propose a generic recursive algorithm for improving image denoising methods. Given the initial denoised image, we suggest repeating the following "SOS" procedure: (i) (S)trengthen the signal by adding the previous denoised image to the ...
Elad, Michael, Romano, Yaniv
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Flashlight CNN Image Denoising [PDF]
2020 28th European Signal Processing Conference (EUSIPCO), 2021 This paper proposes a learning-based denoising method called FlashLight CNN (FLCNN) that implements a deep neural network for image denoising. The proposed approach is based on deep residual networks and inception networks and it is able to leverage many more parameters than residual networks alone for denoising grayscale images corrupted by additive ...
Binh, Pham Huu Thanh +2 more
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Overview of Image Denoising Methods
Jisuanji kexue yu tansuo, 2021 In real scenes, due to the imperfections of equipment and systems or the existence of low-light environments, the collected images are noisy. The images will also be affected by additional noise during the compression and transmission process, which will
LIU Liping, QIAO Lele, JIANG Liucheng
doaj +1 more source
Applied Sciences, 2022 Supervised image denoising methods based on deep neural networks require a large amount of noisy-clean or noisy image pairs for network training. Thus, their performance drops drastically when the given noisy image is significantly different from the ...
Shaoping Xu +5 more
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Image Denoising Using Hybrid Deep Learning Approach and Self-Improved Orca Predation Algorithm
Technologies, 2023 Image denoising is a critical task in computer vision aimed at removing unwanted noise from images, which can degrade image quality and affect visual details.
Rusul Sabah Jebur +4 more
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Impact of Traditional and Embedded Image Denoising on CNN-Based Deep Learning
Applied Sciences, 2023 In digital image processing, filtering noise is an important step for reconstructing a high-quality image for further processing such as object segmentation, object detection, and object recognition.
Roopdeep Kaur +2 more
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Denoising an Image by Denoising Its Curvature Image [PDF]
SIAM Journal on Imaging Sciences, 2014 The first author acknowledges partial support by European Research Council, Starting Grant ref. 306337, and/nby Spanish grants AACC, ref. TIN2011-15954-E, and Plan Nacional, ref. TIN2012-38112. The second author was supported in part by NSF-DMS #0915219.
Marcelo Bertalmío, Stacey Levine
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Multicomponent MR Image Denoising [PDF]
International Journal of Biomedical Imaging, 2009 Magnetic Resonance images are normally corrupted by random noise from the measurement process complicating the automatic feature extraction and analysis of clinical data. It is because of this reason that denoising methods have been traditionally applied to improve MR image quality.
Manjn, José V. +5 more
openaire +4 more sources