Comparison of Multiscale Representations for a Linking-Based Image Segmentation Model

Authors:
Wiro J. Niessen;Koen L. Vincken;Max A. Viergever
Affiliations:
-;-;-
Venue:
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Year:
1996

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Abstract

Different multiscale generators are qualitatively compared with respect to their performance within a multiscale linking model for image segmentation. The linking model used is the hyperstack which was inspired linear scale space theory. We discuss which properties of this paradigm are essential to determine which multiscale representations are suited as input to the hyperstack. If selected, one of the main problems we face is the estimation of the local scale such that the various stacks of images can effectively be compared. For nonlinear multiscale representations, which can be written as modified diffusion equations an upper bound can be achieved synchronizing the evolution parameter. The synchronization is empirically verified counting the number of elliptic patches at corresponding scales. We compare the resulting stacks of images and the segmentation on a test image and a coronal MR brain image.