[PDF] Top 20 La infraestructura de telecomunicaciones y el desarrollo económico de los países
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The UDWT image denoising method based on the PDE model of a convexity-preserving diffusion function
... the image. Considering the nonconvexity property of the diffusion function and the hypersensitivity of the Laplace operator to noise in the Y-K model, a fourth-order PDE image ... See full document
9
Image Denoising Using Anisotropic Diffusion Equations on Reflection and illumination Components of Image
... coherence-enhancing diffusion (CED) model which preserves the coherence structures of ...adaptive diffusion which could sharpen the edges in backward process, in addition to smoothing noises in ... See full document
8
Edge and contrast preserving in total variation image denoising
... regularization model, and then propose a forward-backward diffusion model in the framework of total variation, which can effectively preserve the edges and contrast in TV image ...backward ... See full document
72
A scale-based forward-and-backward diffusion process for adaptive image enhancement and denoising
... in image processing have proven to be fundamental tools for image diffusion and ...heat diffusion equation ...anisotropic diffusion partial differential equation (PDE), with a ... See full document
6
Image denoising by a direct variational minimization
... increasing function of the edge detector Δ u ...the image intensity function is planar, the class of fourth-order PDEs will evolve and settle down to a planar image, if the image ... See full document
7
Image De noising using Optimized Self Similar Patch based Filter
... Image denoising is a familiar domain and researchers have developed various algorithms and methods to overcome ...for denoising of images, the following papers form the basis for the present study ... See full document
10
Adaptive Wavelet Packet Decomposition for Efficient Image Denoising By Using NeighSure Shrink Method
... Originally, Donoho and Johnstone proposed the use of a global threshold uniformly throughout the entire wavelet decomposition tree which was found to be more efficient. Although thresholding with a uniform threshold per ... See full document
25
A Hybrid Image Denoising Method
... and function estimation, factor analysis, modeling and forecasting of time series, functional data analysis and classification, with ranges of application areas in science and engineering ...kernel function ... See full document
138
The Influence of Educational Interventions based on the Continuous Care Model on the Quality of Life of Hemodialysis Patients
... interventions based on the continuous care model on the quality of life of hemodialysis ...selected based on the purposeful sampling method. Based on the findings of the study the ... See full document
9
An Efficient Image Denoising Scheme for Higher Noise Levels using Spatial Domain Filters
... local image variation computes at every pixel value of image, and pixel values are normalized from the neighbouring pixels whose physical characteristics depend on local ...Anisotropic diffusion ... See full document
10
Image Denoising Method Based On Curvelet Transform with Thresholding Functions
... major method of communication now a ...any denoising algorithm is application dependent and it depends upon the type of noise present in the ...Every denoising method has its own assumptions, ... See full document
162
A Modified Adaptive PCA Learning based Method for Image Denoising
... new denoising algorithms for higher image ...noise. Denoising is accomplished by transforming back the processed wavelet coefficients into spatial ...WT denoising includes ridgelet and ... See full document
51
Method of Image Block Denoising Based on Adaptive Total Variation
... biomedical image processing, common biological cell images retains only a few texture details; in addition, researchers care more about the cellular morphology in such images, hence the regions covering cells are ... See full document
10
Morphologic Regularization and Edge-Preserving Super Resolution (Sr) Approach Based On Novel Bregman Algorithm
... SR image reconstruction problem as a deblurring problem with a new robust morphologic regularization ...regularization function based on multi scale opening and closing, which could remove noise ... See full document
10
The value of intravoxel incoherent motion model-based diffusion-weighted imaging for outcome prediction in resin-based radioembolization of breast cancer liver metastases
... Kaplan–Meier method with a log-rank test for statistical significance (categorical para- meters) or a Cox regression model (continuous ...regression model to identify independent predictors of OS and ... See full document
12
Strategic bidding with regard to demand elasticity
... Lena image corrupted with a white Gaussian noise with Standard Deviation (SD) of ...proposed method are compared to the VisuShrink method in the wavelet ... See full document
242
Denoising based on multi level filtering in image processing
... for denoising. They are mostly based on multi-resolution analysis using et ...overall image information is focused on few largest ones due to its sparse ... See full document
97
An Improved Image Denoising Method Based on Wavelet Thresholding
... because denoising most frequently produces smoothed images, reducing their ...denoised image. Our proposed image denoising method is based on thresholding that not only removes ... See full document
236
Image Filter Using with Gaussian Curvature and Total Variation Model
... These types of methods are suffered from the numerical stability requirement. Therefore, the step size in each iteration is limited. They usually need a large number of iterations to converge. Because of that traditional ... See full document
32
Optimization of Gradient Threshold Parameter in Feature Preserving Anisotropic Diffusion for Image Denoising
... local image gradient, so that edges are ...anisotropic diffusion is to evolve from an original image I(x, y), a family of increasingly smoothed images I(x, y, t), based on the following ... See full document
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