TY - GEN
T1 - An algorithm based on augmented Lagrangian method for generalized gradient vector flow computation
AU - Ren, Dongwei
AU - Zuo, Wangmeng
AU - Zhao, Xiaofei
AU - Zhang, Hongzhi
AU - Zhang, Dapeng
PY - 2012/10/10
Y1 - 2012/10/10
N2 - We propose a novel algorithm for the fast computation of generalized gradient vector flow (GGVF) whose high cost of computation has restricted its potential applications on images with large size. We reformulate the GGVF problem as a convex optimization model with equality constraint. Our approach is based on a variable splitting method to obtain an equivalent constrained optimization formulation, which is then addressed with the inexact augmented Lagrangian method (IALM). To further enhance the computational efficiency, IALM is incorporated in a multiresolution approach. Experiments on a set of images with a variety of sizes show that the proposed method can improve the computational speed of the original GGVF by one or two order of magnitude, and is comparable with the multigrid GGVF (MGGVF) method in terms of the computational efficiency.
AB - We propose a novel algorithm for the fast computation of generalized gradient vector flow (GGVF) whose high cost of computation has restricted its potential applications on images with large size. We reformulate the GGVF problem as a convex optimization model with equality constraint. Our approach is based on a variable splitting method to obtain an equivalent constrained optimization formulation, which is then addressed with the inexact augmented Lagrangian method (IALM). To further enhance the computational efficiency, IALM is incorporated in a multiresolution approach. Experiments on a set of images with a variety of sizes show that the proposed method can improve the computational speed of the original GGVF by one or two order of magnitude, and is comparable with the multigrid GGVF (MGGVF) method in terms of the computational efficiency.
KW - augmented Lagrangian method
KW - convex optimization
KW - Generalized gradient vector flow
KW - multiresolution method
UR - http://www.scopus.com/inward/record.url?scp=84867126698&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33506-8_22
DO - 10.1007/978-3-642-33506-8_22
M3 - Conference article published in proceeding or book
SN - 9783642335051
T3 - Communications in Computer and Information Science
SP - 170
EP - 177
BT - Pattern Recognition - Chinese Conference, CCPR 2012, Proceedings
T2 - 2012 5th Chinese Conference on Pattern Recognition, CCPR 2012
Y2 - 24 September 2012 through 26 September 2012
ER -