Paper
27 June 1988 Utilization Of Fractional Brownian Motion In Constrained Least-Squares Restoration Of Medical Images
Walter S. Kuklinski
Author Affiliations +
Abstract
Constrained least-squares techniques have been used to produce a well known class of image restoration algorithms. These techniques typically involve minimizing a linear operator on a vector representation of an image, subject to a constraint. For cases where an equality constraint is appropriate the method of Lagrange multipliers can be used to produce a restored image. In this work a fractal textural model,fractional Brownian motion, is used to represent images of interest. Using a variance fractal dimension estimator a non-linear operator, that represents the squared difference between the fractal dimension of the restored image and an a priori value is minimized, subject to the constraint that the norm of the residual between the restored image and available measurement equal the norm of the additive noise.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Walter S. Kuklinski "Utilization Of Fractional Brownian Motion In Constrained Least-Squares Restoration Of Medical Images", Proc. SPIE 0914, Medical Imaging II, (27 June 1988); https://doi.org/10.1117/12.968651
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KEYWORDS
Fractal analysis

Image restoration

Image segmentation

Medical imaging

Statistical analysis

Image processing

Motion models

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