This paper deals with size-sensitive multiresolution decomposition using adaptive morphological filters with a flat structuring element. This type of decomposition generates a set of images, each containing elements of the original image with a specific size. The authors propose to extract a set of dominant shapes contained in the original image and to assess the size of a particular element by comparison with this set of dominant shapes. This approach is particularly suitable for texture images where dominant shapes are actually present. In a first step, it is shown how a flat structuring element of a morphological filter can be adapted to optimize a statistical criterion such as the mean square error. The approach is suitable for any morphological filters and the proposed algorithms are simple. Moreover, they can be easily modified to achieve a size-constrained optimization of the structuring element, which is an attractive solution for the extraction of dominant shapes. Finally,adaptive morphological filters are used in a multiresolution decomposition scheme which sorts the various components as a function of their size while taking into account the presence of dominant shapes. Two particular applications are presented. They address the problems of noise removal and texture defect detection.

Date Published: 1 July 1991
PDF: 12 pages
Proc. SPIE 1568, Image Algebra and Morphological Image Processing II, (1 July 1991); doi: 10.1117/12.49883

Published in SPIE Proceedings Vol. 1568:
Image Algebra and Morphological Image Processing II
Paul D. Gader; Edward R. Dougherty, Editor(s)