Learning-based mathematical morphology in color image processing
Hao Yu Zhou · 2007
Mathematical Morphology is a powerful nonlinear image processing tool and is widely used in image segmentation, image filtering, shape representation, image measurement and so on. Most of the morphological operation based image processing approaches are developed for binary and grayscale images. Recently, since the color image has become the dominant image format nowadays and contains much more information than grayscale image, a problem of significant challenging in mathematical morphology is to extend basic morphological operations and their applications into color image processing area. This thesis mainly focuses on extending the existing basic morphological operators and their applications into color image processing area, by incorporating supervised and unsupervised learning techniques. The major contributions are summarized below: