Image segmentation via image decomposition and fuzzy region competition

摘要

Image segmentation is a fundamental process in most image processing, pattern recognition, and computer vision applications. It separates the desired objects from the set of desired and undesired objects in an image. This paper presents such an image segmentation method. The author presents an image segmentation model described in three terms: regularization, data fidelity, and decomposing an image into two parts, piecewise smooth and oscillating texture. This model "integrates image decomposition and image segmentation into a unified model within [a] fuzzy region competition framework." He further divides the minimization problem into four subproblems: dictionary learning and structure-texture decomposition, optimization of the piecewise constant image, membership functions, and auxiliary functions.