A convex relaxation framework consisting of a primal-dual alternative algorithm for solving ℓ0 sparsity-induced optimization problems with application to signal recovery based image restoration.
Zhengwei ShenQian ChenFan YangPublished in: J. Comput. Appl. Math. (2023)
Keyphrases
- primal dual
- image restoration
- convex optimization
- cost function
- optimization problems
- linear programming
- objective function
- convergence rate
- convex relaxation
- total variation
- dynamic programming
- np hard
- globally optimal
- gaussian noise
- expectation maximization
- approximation algorithms
- worst case
- computational complexity
- optimal solution
- semidefinite programming
- computer vision
- sparse approximation
- linear program
- bayesian framework
- image classification
- simulated annealing
- evolutionary algorithm
- interior point methods
- image processing