scholarly journals Image Denoising viaL0Gradient Minimization with Effective Fidelity Term

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Wenxue Zhang ◽  
Yongzhen Cao ◽  
Rongxin Zhang ◽  
Lingling Li ◽  
Yunlei Wen
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
State Of The Art ◽  
Least Square Method ◽  
Least Square ◽  
Image Smoothing ◽  
Piecewise Constant ◽  
Moving Least Square ◽  
Fidelity Term ◽  
Tv Model

TheL0gradient minimization (LGM) method has been proposed for image smoothing very recently. As an improvement of the total variation (TV) model which employs theL1norm of the gradient, the LGM model yields much better results for the piecewise constant image. However, just as the TV model, the LGM model also suffers, even more seriously, from the staircasing effect and the inefficiency in preserving the texture in image. In order to overcome these drawbacks, in this paper, we propose to introduce an effective fidelity term into the LGM model. The fidelity term is an exemplar of the moving least square method using steering kernel. Under this framework, these two methods benefit from each other and can produce better results. Experimental results show that the proposed scheme is promising as compared with the state-of-the-art methods.

scholarly journals A Nonmonotone Gradient Algorithm for Total Variation Image Denoising Problems

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Peng Wang ◽  
Shifang Yuan ◽  
Xiangyun Xie ◽  
Shengwu Xiong
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Gradient Method ◽  
State Of The Art ◽  
Gradient Algorithm ◽  
Projected Gradient Method ◽  
New Strategy ◽  
A New Technique ◽  
Tv Model ◽  
Better Than

The total variation (TV) model has been studied extensively because it is able to preserve sharp attributes and capture some sparsely critical information in images. However, TV denoising problem is usually ill-conditioned that the classical monotone projected gradient method cannot solve the problem efficiently. Therefore, a new strategy based on nonmonotone approach is digged out as accelerated spectral project gradient (ASPG) for solving TV. Furthermore, traditional TV is handled by vectorizing, which makes the scheme far more complicated for designing algorithms. In order to simplify the computing process, a new technique is developed in view of matrix rather than traditional vector. Numerical results proved that our ASPG algorithm is better than some state-of-the-art algorithms in both accuracy and convergence speed.

scholarly journals Exact solutions for the total variation denoising problem of piecewise constant images in dimension one

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Riccardo Cristoferi
Keyword(s):  
Exact Solution ◽  
Exact Solutions ◽  
Total Variation ◽  
Piecewise Constant ◽  
Geometrical Properties ◽  
Total Variation Denoising ◽  
Fidelity Term ◽  
Dimension One

AbstractA method for obtaining the exact solution for the total variation denoising problem of piecewise constant images in dimension one is presented. The validity of the algorithm relies on some results concerning the behavior of the solution when the parameter λ in front of the fidelity term varies. Albeit some of them are well-known in the community, here they are proved with simple techniques based on qualitative geometrical properties of the solutions.

scholarly journals Superresolution of 3-D computational integral imaging based on moving least square method

2014 ◽  
Vol 22 (23) ◽  
pp. 28606 ◽  
Author(s):  
Hyein Kim ◽  
Sukho Lee ◽  
Taekyung Ryu ◽  
Jungho Yoon
Keyword(s):  
Least Square Method ◽  
Least Square ◽  
Integral Imaging ◽  
Moving Least Square ◽  
Computational Integral Imaging

Basic Study on Trend Prediction for Style Design

2008 ◽  
Author(s):  
Shinya Yoshida ◽  
Hideki Aoyama
Keyword(s):  
Product Design ◽  
Least Square Method ◽  
Least Square ◽  
Concept Design ◽  
Trend Prediction ◽  
Basic Study ◽  
Moving Least Square ◽  
And Function ◽  
Eigenvalue And Eigenvector ◽  
Near Future

With diversification of consumer taste, appearance shape together with functionality contributes to the appeal of a product vastly. Concept design and industrial design therefore serve as an important process in product development. These designs are difficult to perform based on theoretical backing, since appearance shape design is a creative activity which depends on a designer’s aesthetic sense strongly. When embodying a product shape, naturally design is determined not only by a designer’s sensitivity but by use and function of a product as well. It is also important to investigate designs desired by consumers, and reflect all of this in the product design. The ability to predict consumer taste trends therefore greatly aids product design. In this research, the prototype models of a product in trend every year were made by multiplying weights according to the number of a product sold in the past to calculate that the rate of exaggeration of prototype models of each year to all whole prototype models. The straight extrapolation of the Spline method was applied to the exaggeration vector, and the technique of predicting shapes preferred by consumers in the near future using that method was proposed. Moreover the eigenspace method was applied to similar product shapes to propose the technique of grasping the features of shape for every year by computing the eigenvalue and eigenvector of the coordinates of the points of the shapes as well as the technique of predicting shapes which consumers will prefer in the near future by using the Linear function of Moving Least Square method.

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