Image segmentation using some piecewise constant level set methods with MBO type of projection
In this work, we are trying to propose fast algorithms for Mumford-Shah image segmentation using some recently proposed piecewise constant level set methods (PCLSM). Two variants of the PCLSM will be considered in this work. The first variant, which we call the binary level set method, needs a level set function which only takes values I to identify the regions. The second variant only needs to use one piecewise constant level set function to identify arbitrary number of regions. For the Murnford-Shah image segmentation model with these new level set methods, one needs to minimize some smooth energy functionals under some constrains. A penalty method will be used to deal with the constraint. AOS (additive operator splitting) and MOS (Multiplicative operator splitting) schemes will be used to solve the Euler-Lagrange equations for the minimization problems. By doing this, we obtain some algorithms which are essentially applying the MBO scheme for Our segmentation models. Advantages and disadvantages are discussed for the proposed schemes.
image segmentation level set method total variation regularization phase field model