Recent results have shown that denoising an image with the Rudin, Osher and Fatemi (ROF) total variation model can be accomplished by solving a series of binary optimization problems. We observe that this fact can be used in the other direction. The procedure is applied to the two-phase, piecewise constant Mumford-Shah functional, where an image is approximated with a function taking only two values. When the difference between the two levels is kept constant, a global optimum can be found efficiently. This allows us to solve the full problem with branch and bound in only one dimension.
|Conference||Swedish Symposium on Image Analysis (SSBA) 2009|
|Period||2009/03/19 → 2009/03/20|
- Computer Vision and Robotics (Autonomous Systems)
- total variation
- image processing