Influence to new formulas gradient for removing impulse noise images
Бесплатный доступ
In conjugate gradient techniques, the conjugate formula is often the primary point of concentration. The conjugate gradient technique is used to solve problems that arise during the process of picture restoration. By using the quadratic model, a brand-new coefficient conjugate will be produced for the operation. The algorithms demonstrate both local and global convergence and descent. The numerical testing revealed that the newly developed method is much superior to the one that came before it. The recently created conjugate gradient strategy has better performance than the FR conjugate gradient technique, which is the industry standard.
Influence to formula gradient, convergence property, impulse noise reduction for images
Короткий адрес: https://sciup.org/147243953
IDR: 147243953 | DOI: 10.14529/mmp240106
Список литературы Influence to new formulas gradient for removing impulse noise images
- Wei Xue, Junhong Ren, Xiao Zheng, Zhi Liu, Yueyong Lianga. A New DY Conjugate Gradient Method and Applications to Image Denoising. IEICE Transactions on Information and Systems, 2018, vol. 101, no. 12, pp. 2984-2990. DOI: 10.1587/transinf.2018EDP7210
- Fletcher R. Practical Methods of Optimization. Chichester, N.Y., Brisbane, Toronto, Singapore, John Wiley and Sons, 2013. DOI: 10.1002/9781118723203
- Fletcher R., Reeves C.M. Function Minimization by Conjugate Gradients. Computer Journal, 1964, vol. 7, no. 2, pp. 149-154. DOI: 10.1093/comjnl/7.2.149
- Yasushi N., Hideaki I. Conjugate Gradient Methods using Value of Objective Function for Unconstrained Optimization. Optimization Letters, 2012, vol. 6, pp. 941-955. DOI: 10.23851/mjs.v27i5.170
- Polak E., Ribiere G. Note sur la Convergence de Methodes de Directions Conjuguees. Revue Francaise D'Informatique et de Recherche Operationnelle. Serie Rouge, 1969, vol. 3, no. 16, pp. 35-43. (in French)
- Wolfe P. Convergence Conditions for Ascent Methods. II: Some Corrections. Society for Industrial and Applied Mathematics Review, 1971, vol. 13, no. 2, pp. 185-188. DOI: 10.1137/1011036
- Wolfe P. Convergence Conditions for Ascent Methods. Society for Industrial and Applied Mathematics Review, 1969, vol. 11, no. 2, pp. 226-235. DOI: 10.1137/1011036
- Hassan B.A., Abdullah Z.M., Jabbar H.N. A Descent Extension of the Dai-Yuan Conjugate Gradient Technique. Indonesian Journal of Electrical Engineering and Computer Science, 2019, vol. 16, no. 2, pp. 661-668. DOI: 10.11591/ijeecs.v16.i2.pp661-668
- Dai Uhong, Han Jiye, Liu Guanghui, Sun Defeng, Yin Hongxia, Yuan Ya-Xiang. Convergence Properties Of Nonlinear Conjugate Gradient Methods. Society for Industrial and Applied Mathematics. Journal on Optimization, 2000, vol. 10, no. 2, pp. 345-358. DOI: 10.1137/S1052623494268443
- Liu Y., Storey C. Efficient Generalized Conjugate Gradient Algorithms, Part 1: Theory. Journal of Optimization Theory and Applications, 1991, vol. 69, no. 1, pp. 129-137. DOI: 10.1007/BF00940464
- Jabbar H.N., Hassan B.A. Two-Versions of Descent Conjugate Gradient Methods for Large-Scale Unconstrained Optimization. Indonesian Journal of Electrical Engineering and Computer Science, 2021, vol. 22, no. 3, p. 1643. DOI: 10.11591/ijeecs.v22.i3.pp1643-1649
- Hassan B.A., Younis M.S., Taha M.W., Ibrahim A.H. A New Type of Step Sizes for Unconstrained Optimization. in Journal of Physics: Conference Series, 2021, vol. 1999, no. 1, article ID: 12099. DOI: 10.1088/1742-6596/1999/1/012099
- Stiefel E. Methods of Conjugate Gradients for Solving Linear Systems. Journal of Research of the National Bureau of Standards, 1952, vol. 49, pp. 409-435. DOI: 10.6028/JRES.049.044
- Hassan B.A., Sulaiman R.M. A New Class of Self-Scaling for Quasi-Newton Method Based on the Quadratic Model. Indonesian Journal of Electrical Engineering and Computer Science, 2021, vol. 21, no. 3, pp. 1830-1836. DOI: 10.11591/ijeecs.v21.i3.pp1830-1836
- Zhanga Jianzhong, Xu Chengxian. Properties and Numerical Performance of Quasi-Newton Methods with Modified Quasi-Newton Equations. Journal of Computational and Applied Mathematics, 2001, vol. 137, no. 2, pp. 269-278. DOI: 10.1016/S0377-0427(00)00713-5
- Nazareth L. A Relationship Between the BFGS and Conjugate Gradient Algorithms and its Implications for New Algorithms. Society for Industrial and Applied Mathematics. Journal on Numerical Analysis, 1979, vol. 16, no. 5, pp. 794-800. DOI: 10.1137/0716059
- Hassan B.A., Dahawi H.O., Younus A.S. A New Kind of Parameter Conjugate Gradient for Unconstrained Optimization. Indonesian Journal of Electrical Engineering and Computer Science, 2020, vol. 17, no. 1, p. 404. DOI: 10.11591/ijeecs.v17.i1.pp404-411
- Abubakar A.B., Kumam P., Ibrahim A.H., Chaipunya P., Ran S.A. New Hybrid Three-Term Spectral-Conjugate Gradient Method for Finding Solutions of Nonlinear Monotone Operator Equations with Applications. Mathematics and Computers in Simulation, 2022, vol. 201, pp. 670-683. DOI: 10.1016/j.matcom.2021.07.005
- Dai Yu-Hong, Yuan Ya-xiang. A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property. Society for Industrial and Applied Mathematics. Journal on Optimization, 1999, vol. 10, no. 1, pp. 177-182. DOI: 10.1137/S1052623497318992
- Yu Gaohang, Huang Jinhong, Zhou Yi. A Descent Spectral Conjugate Gradient Method for Impulse Noise Removal. Applied Mathematics Letters, 2010, vol. 23, no. 5, pp. 555-560. DOI: 10.1016/j.aml.2010.01.010
- Ibrahim A.H., Kumam P., Sun M., Chaipunya P., Abubakar A.B. Projection Method with Inertial Step for Nonlinear Equations: Application to Signal Recovery. Journal of Industrial and Management Optimization, 2022, vol. 19, no. 1, pp. 30-55. DOI: 10.3934/jimo.2021173
- Wu Caiying, Chen Guoqing. New Type of Conjugate Gradient Algorithms for Unconstrained Optimization Problems. Journal of Systems Engineering and Electronics, 2010, vol. 21, no. 6, pp. 1000-1007. DOI: 10.3969/j.issn.1004-4132.2010.06.012
- Andrei N. An Unconstrained Optimization Test Functions Collection. Advanced Modeling and Optimization, 2008, vol. 10, no. 1, pp. 147-161.
- Nocedal J., Wright S.J. Numerical Optimization. N.Y., Springer, 1999. DOI: 10.1007/0-387-22742-3_18
- Hassan B.A., Jabbar H.N., Laylani Y.A. Upscaling Parameters for Conjugate Gradient Method in Unconstrained Optimization. Journal of Interdisciplinary Mathematics, 2023, vol. 26, no. 6, pp. 1171-1180. DOI: 10.47974/JIM-1615