Results 1 to 10 of about 13,906,445 (282)
Variational Anisotropic Gradient-Domain Image Processing [PDF]
Journal of Imaging, 2021 Gradient-domain image processing is a technique where, instead of operating directly on the image pixel values, the gradient of the image is computed and processed. The resulting image is obtained by reintegrating the processed gradient. This is normally
Ivar Farup
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Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design
Sensors, 2023 In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction. The combination of VAE and various machine learning frameworks has also worked effectively in different ...
Hugo Wai Leung Mak +2 more
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Research on Image Dehazing Based on Dark Channel Prior and Variational Regularization [PDF]
Jisuanji gongcheng, 2021 The existing foggy image processing methods can achieve good dehazing effect, but some details are often lost, and noise amplification is easy to occur in the noisy areas.In order to solve these problems, a new variational dehazing model, H-TVBH, is ...
ZHAO Hui, WEI Weibo, PAN Zhenkuan, JI Lianshun
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A four directions variational method for solving image processing problems [PDF]
Iranian Journal of Numerical Analysis and Optimization, 2020 In this paper, based on a discrete total variation model, a modified discretization of total variation (TV) is introduced for image processing problems.
Alireza H., E.E. Esfahani
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A Study of Adaptive Fractional-Order Total Variational Medical Image Denoising
Fractal and Fractional, 2022 Following the traditional total variational denoising model in removing medical image noise with blurred image texture details, among other problems, an adaptive medical image fractional-order total variational denoising model with an improved sparrow ...
Yanzhu Zhang +3 more
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Impact of process variations on computers used for image processing [PDF]
2012 IEEE International Symposium on Circuits and Systems, 2012 Manufacturing process variations (PV) of transistors in the deep-submicron regime present the single biggest design challenge for large die size VLSI circuits such as processor arrays, GPUs, and FPGAs. However, there are a few applications in signal processing, such as image processing, and speech processing, where errors in computation by the ...
Suraj Sindia +3 more
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Weighted nonlocal total variation in image processing [PDF]
Methods and Applications of Analysis, 2019 In this paper, a novel weighted nonlocal total variation (WNTV) method is proposed. Compared to the classical nonlocal total variation methods, our method modifies the energy functional to introduce a weight to balance between the labeled sets and unlabeled sets.
Haohan Li +2 more
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Colour image segmentation based on a convex K‐means approach
IET Image Processing, 2021 Image segmentation is a fundamental and challenging task in image processing and computer vision. The colour image segmentation is attracting more attention as the colour image provides more information than the grey image. A variational model based on a
Tingting Wu +4 more
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Extensible Gaussian Mixture Model for Image Prior Modeling [PDF]
Jisuanji gongcheng, 2020 To address the inextensible fixed number of components in image prior modeling based on Gaussian Mixture Model(GMM),this paper proposes an extensible GMM model based on Dirichlet Process(DP).Through the addition and merging mechanism of cluster ...
ZHANG Mohua, PENG Jianhua
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Multiplicative Noise Removal via a Novel Variational Model
EURASIP Journal on Image and Video Processing, 2010 Multiplicative noise appears in various image processing applications, such as synthetic aperture radar, ultrasound imaging, single particle emission-computed tomography, and positron emission tomography.
Li-Li Huang, Liang Xiao, Zhi-Hui Wei
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