Name
Abstract | ||
|---|---|---|
Restoring binary images is a problem which arises in various ap- plication fields. In our paper, this problem is considered in a vari- ational framework: the sought-after solution minimizes an energy. Energies defined over the set of the binary images are inevitably nonconvex and there are no general methods to calculate the global minimum, while local minimziers are very often of limited inter- est. In this paper we define the restored image as the global min- imizer of the total-variation (TV) energy functional constrained to the collection of all binary-valued images. We solve this con- strained non-convex optimization problem by deriving another func- tional which is convex and whose (unconstrained) minimum is proven to be reached for the global minimizer of the binary con- strained TV functional. Practical issues are discussed and a nu- merical example is provided. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICIP.2005.1529702 | Image Processing, 2005. ICIP 2005. IEEE International Conference |
Keywords | Field | DocType |
image restoration,binary image restoration,nonconvex optimization,total-variation energy | Mathematical optimization,Computer science,Binary image,Regular polygon,Energy functional,Image restoration,Optimization problem,Binary number | Conference |
Volume | ISSN | ISBN |
1 | 1522-4880 | 0-7803-9134-9 |
Citations | PageRank | References |
9 | 0.62 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tony F. Chan | 1 | 8733 | 659.77 |
| Selim Esedoglu | 2 | 1000 | 49.59 |
| Mila Nikolova | 3 | 1792 | 105.71 |