Paper
1 July 1991 Multiscale analysis based on mathematical morphology
Yi Lu, Robert C. Vogt III
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Abstract
In the field of computer vision, multiscale analysis has received much attention in the past decade. In particular, Gaussian scale space has been studied extensively and has proven to be effective in multiscale analysis. Recent research has shown that morphological openings or openings or closings with isotropic structuring elements such as disks define a scale space, where the radius of a disk r is the scale parameter which changes continuously from 0 to infinity. The behaviors of objects described by the morphological scale space provide strong knowledge for multiscale analysis. Based on the theory of morphological scale space, we address in this paper the two fundamental problems in multiscale analysis: (1) how to select proper scale parameters for various applications, and (2) how to integrate the information filtered at multiscales. We propose two algorithms, binary morphological multiscale analysis (BMMA) and gray-scale morphological multiscale analysis (GMMA), for extracting desired regions from binary and gray images.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yi Lu and Robert C. Vogt III "Multiscale analysis based on mathematical morphology", Proc. SPIE 1568, Image Algebra and Morphological Image Processing II, (1 July 1991); https://doi.org/10.1117/12.49882
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Cited by 1 scholarly publication.
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KEYWORDS
Image filtering

Binary data

Image processing

3D image processing

Analytical research

3D modeling

Smoothing

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