A linearly convergent first-order algorithm for total variation minimisation in image processing.
We introduce a new formulation for total variation minimisation in image denoising. We also present a linearly convergent first-order method for solving this reformulated problem and show that it possesses a nearly dimension-independent iteration complexity bound.
Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611, USA.
Cong D
CD
Dang
Software School, Fudan University, Shanghai 201203, China.
Kaiyu
K
Dai
Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611, USA.
Guanghui
G
Lan
D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016014:Linear Models; D059629:Signal-To-Noise Ratio
complexity; first–order methods; image denoising; image processing; linear rate of convergence; reformulation; total variation