Abstract

Pyramidal image processing (PIP) is a form of multiresolution analysis in which a primary image is decomposed into a set of different resolution image copies. Pyramidal processing aims to extract and interpret significant features of an image appearing at different resolutions. Because of using a large number of multidimensional convolutions, the existing digital software PIP implementations are very time-consuming. Recently, morphological filtering (MF)-based image processing and analysis, because of its simplicity of operation and its direct relationship to the shapes of an image, have been widely studied. Using a MF method, the implementation of PIP is proposed. By using a set of well-structured masks, a primary image is decomposed into a sequence of resolution image copies. Pipelined and parallel algorithms are suggested for these morphological PIP (MPIP). Using various linear and nonlinear optical methods, various optical MPIP structures are described.

© 1988 Optical Society of America