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Proceedings Paper

Application of a new method for analyzing images: two-dimensional non-linear additive decomposition
Author(s): Michael A. Zaccaria; David M. Brudnoy; John E. Stasenko
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Paper Abstract

This paper documents the application of a new image processing algorithm, two-dimensional non-linear additive decomposition (NLAD), which is used to identify regions in a digital image whose gray-scale (or color) intensity is different than the surrounding background. Standard image segmentation algorithms exist that allow users to segment images based on gray-scale intensity and/or shape. However, these processing techniques do not adequately account for the image noise and lighting variation that typically occurs across an image. NLAD is designed to separate image noise and background from artifacts thereby providing the ability to consistently evaluate images. The decomposition techniques used in this algorithm are based on the concepts of mathematical morphology. NLAD emulates the human capability of visually separating an image into different levels of resolution components, denoted as 'coarse', 'fine', and 'intermediate.' Very little resolution information overlaps any two of the component images. This method can easily determine and/or remove trends and noise from an image. NLAD has several additional advantages over conventional image processing algorithms, including no need for a transformation from one space to another, such as is done with Fourier transforms, and since only finite summations are required, the calculational effort is neither extensive nor complicated.

Paper Details

Date Published: 25 August 2006
PDF: 12 pages
Proc. SPIE 6315, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX, 63150N (25 August 2006); doi: 10.1117/12.690310
Show Author Affiliations
Michael A. Zaccaria, Lockheed Martin Co. (United States)
David M. Brudnoy, Lockheed Martin Co. (United States)
John E. Stasenko, Lockheed Martin Co. (United States)


Published in SPIE Proceedings Vol. 6315:
Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX
Gerhard X. Ritter; Mark S. Schmalz; Junior Barrera; Jaakko T. Astola, Editor(s)

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