New proximal type algorithms for convex minimization and its application to image deblurring

  • Kesornprom, Suparat
  • Cholamjiak, Prasit
  • Park, Choonkil
Citations

WEB OF SCIENCE

3
Citations

SCOPUS

4

초록

In this work, we are interested in solving a convex minimization problem in real Hilbert spaces. We propose a new modified proximal algorithm using the inertial extrapolation and the linesearch technique. Its weak convergence theorems are established under mild conditions. Numerical experiments are presented to illustrate the performance of the proposed algorithm in image deblurring.

키워드

Convex minimization problemForward-backward methodLinesearch ruleInertial methodWeak convergenceSPLIT FEASIBILITYCONVERGENCESHRINKAGE
제목
New proximal type algorithms for convex minimization and its application to image deblurring
저자
Kesornprom, SuparatCholamjiak, PrasitPark, Choonkil
DOI
10.1007/s40314-022-02042-7
발행일
2022-10
유형
Article
저널명
Computational and Applied Mathematics
41
7