A sufficient descent conjugate gradient method for impulse noise removal

: In this paper, we introduce a modified PRP-type conjugate gradient (CG) method for impulse noise removal in the second phase of the two-phase method. A nice property of the scheme is that the search direction at each iteration satisfies the sufficient descent condition independent of any line search. Under the Armijo-type line search, its global convergence result is proved. Numerical comparison is given to illustrate that the proposed method for removing impulse noise is promising.

[1]  Jianghua Yin,et al.  A generalized hybrid CGPM-based algorithm for solving large-scale convex constrained equations with applications to image restoration , 2021, J. Comput. Appl. Math..

[2]  Jinkui Liu,et al.  A gradient‐type iterative method for impulse noise removal , 2020, Numer. Linear Algebra Appl..

[3]  Chao Zeng,et al.  Non-Lipschitz Models for Image Restoration with Impulse Noise Removal , 2019, SIAM J. Imaging Sci..

[4]  Yongfei Wu,et al.  A Retinex modulated piecewise constant variational model for image segmentation and bias correction , 2018 .

[5]  Yi Zhou,et al.  A descent spectral conjugate gradient method for impulse noise removal , 2010, Appl. Math. Lett..

[6]  W. Cheng A Two-Term PRP-Based Descent Method , 2007 .

[7]  Raymond H. Chan,et al.  A Detection Statistic for Random-Valued Impulse Noise , 2007, IEEE Transactions on Image Processing.

[8]  Raymond H. Chan,et al.  Minimization of detail-preserving regularization functional by Newton's method with continuation , 2005, IEEE International Conference on Image Processing 2005.

[9]  Richard A. Haddad,et al.  Adaptive median filters: new algorithms and results , 1995, IEEE Trans. Image Process..

[10]  T. Nodes,et al.  The Output Distribution of Median Type Filters , 1984, IEEE Trans. Commun..

[11]  Thomas S. Huang,et al.  A fast two-dimensional median filtering algorithm , 1979 .

[12]  P. J. Huber Robust Regression: Asymptotics, Conjectures and Monte Carlo , 1973 .

[13]  Ting-Zhu Huang,et al.  Three-dimensional fractional total variation regularized tensor optimized model for image deblurring , 2021, Appl. Math. Comput..

[14]  Boris Polyak The conjugate gradient method in extreme problems , 2015 .

[15]  Jian-Feng Cai,et al.  Minimization of an Edge-Preserving Regularization Functional by Conjugate Gradient Type Methods , 2007 .

[16]  Michael I. Miller,et al.  Landmark Matching via Large Deformation Diffeomorphisms on the Sphere , 2004, Journal of Mathematical Imaging and Vision.