1 April 2003 Morphological characterization of dithering masks
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We present some novel tools for the analysis of blue-noise binary patterns. Unlike most of the existing methods that evaluate the frequency content of a given mask or its lower order statistics, our new metrics characterize the morphological content of a mask that is quantified using simple one-pass filtering. An analytical filter expression is given. As a result, one can balance the structural content of the mask—diagonal, vertical, and horizontal interconnections of the majority (or minority) pixels—at the same level. In addition, it is possible to improve the overall mask quality by prescribing the occurrence of morphological shapes of connected pixels. Examples of morphological analysis are given to demonstrate the different qualities of blue-noise and white-noise patterns.
©(2003) Society of Photo-Optical Instrumentation Engineers (SPIE)
Vladimir Misic and Kevin J. Parker "Morphological characterization of dithering masks," Journal of Electronic Imaging 12(2), (1 April 2003). https://doi.org/10.1117/1.1556766
Published: 1 April 2003
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Cited by 2 scholarly publications.
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KEYWORDS
Binary data

Halftones

Image filtering

Visualization

Convolution

Detection and tracking algorithms

Digital filtering

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