Analysis of Half-Quadratic Minimization Methods for Signal and Image Recovery


We address the minimization of regularized convex cost functions which are customarily used for edge-preserving restoration and reconstruction of signals and images. In order to accelerate computation, the multiplicative and the additive half-quadratic reformulation of the original cost-function have been pioneered in Geman & Reynolds (1992) and Geman… (More)
DOI: 10.1137/030600862

15 Figures and Tables



Citations per Year

332 Citations

Semantic Scholar estimates that this publication has 332 citations based on the available data.

See our FAQ for additional information.

  • Presentations referencing similar topics