Multi-resolution relaxation

摘要

Several types of iterative methods can be used to segment the pixels in an image into light and dark regions; these include “relaxation” methods of probability adjustment and steepest-descent methods of cost function minimization. Conventionally, these methods operate on the image at a single resolution. This paper investigates the possibility of using these approaches at two (or more) resolutions in order to reduce their computational cost—e.g. first obtain an approximate solution by iterating at low resolution, then refine the solution using a few iterations at high resolution.