Results 51 to 60 of about 39,050 (216)
A Second-Order Method for Removing Mixed Noise from Remote Sensing Images
Sensors, 2023 Remote sensing image denoising is of great significance for the subsequent use and research of images. Gaussian noise and salt-and-pepper noise are prevalent noises in images.
Ying Zhou +6 more
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ANALYSIS AND PREDICTION OF FILTERING EFFICIENCY USING NO-REFERENCE IMAGE VISUAL QUALITY METRICS
Радіоелектронні і комп'ютерні системи, 2018 Images are subject to noise during acquisition, transmission and processing. Image denoising is highly desirable, not only to provide better visual quality, but also to improve performance of the subsequent operations such as compression, segmentation ...
Андрей Сергеевич Рубель +1 more
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Dual-domain image denoising [PDF]
2013 IEEE International Conference on Image Processing, 2013 Image denoising methods have been implemented in both spatial and transform domains. Each domain has its advantages and shortcomings, which can be complemented by each other. State-of-the-art methods like block-matching 3D filtering (BM3D) therefore combine both domains. However, implementation of such methods is not trivial.
Matthias Zwicker, Claude Knaus
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Multi-task learning with self-learning weight for image denoising
Journal of Engineering and Applied ScienceBackground Image denoising technology removes noise from the corrupted image by utilizing different features between image and noise. Convolutional neural network (CNN)-based algorithms have been the concern of the recent progress on diverse image ...
Qian Xiang, Yong Tang, Xiangyang Zhou
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A New Nonlinear Diffusion Equation Model for Noisy Image Segmentation
Advances in Mathematical Physics, 2016 Image segmentation and image denoising are two important and fundamental topics in the field of image processing. Geometric active contour model based on level set method can deal with the problem of image segmentation, but it does not consider the ...
Bo Chen +5 more
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Fully Symmetric Convolutional Network for Effective Image Denoising
Applied Sciences, 2019 Neural-network-based image denoising is one of the promising approaches to deal with problems in image processing. In this work, a deep fully symmetric convolutional⁻deconvolutional neural network (FSCN) is proposed for image denoising.
Steffi Agino Priyanka, Yuan-Kai Wang
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Denoising of Image Gradients and Total Generalized Variation Denoising [PDF]
Journal of Mathematical Imaging and Vision, 2018 We revisit total variation denoising and study an augmented model where we assume that an estimate of the image gradient is available. We show that this increases the image reconstruction quality and derive that the resulting model resembles the total generalized variation denoising method, thus providing a new motivation for this model.
Birgit Komander +2 more
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Deep learning informed diffusion equation model for image denoising
IET Image ProcessingImage denoising is one of the fundamental problems in image processing. Convolutional neural network (CNN) based denoising approaches have achieved better performance than traditional methods, such as STROLLR and BM3D.
Yao Li +3 more
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Image denoising: pointwise adaptive approach [PDF]
The Annals of Statistics, 2003 The paper is concerned with the problem of image denoising. We consider the case of black-white type images consisting of a finite number of regions with smooth boundaries and the image value is assumed to be piecewise constant within each region. New method of image denoising is proposed which is adaptive (assumption free) to the number of regions and
Jörg Polzehl, Vladimir Spokoiny
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Boosting of Denoising Effect with Fusion Strategy
Applied Sciences, 2020 Image denoising, a fundamental step in image processing, has been widely studied for several decades. Denoising methods can be classified as internal or external depending on whether they exploit the internal prior or the external noisy-clean image ...
Fangjia Yang, Shaoping Xu, Chongxi Li
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