Quantitative analysis of blue noise mask generation

Meng Yao; Lan Gao; Kevin J. Parker

doi:10.1117/12.233304

27 February 1996 Quantitative analysis of blue noise mask generation

Meng Yao, Lan Gao, Kevin J. Parker

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233304
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

Abstract

The blue noise mask (BNM) is a stochastic screen that produces visually pleasing blue noise. In its construction, a filter is applied to a given dot pattern to identify clumps in order to add or remove dots and thereby generate a correlated binary pattern for the next level. But up to now, all the filters were selected on a qualitative basis. There is no reported work describing precisely how the filtering and selection of dots affects the perceived error of the binary pattern. In this paper, we give a strict mathematical analysis of the BNM construction based on a human visual model, which provides insights to the filtering process and also prescribes the locations of the dots that will result in a binary pattern of minimum perceived error when swapped. The analysis also resolves some unexplained issues noticed by other researchers.

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Meng Yao, Lan Gao, and Kevin J. Parker "Quantitative analysis of blue noise mask generation", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233304

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KEYWORDS

Binary data

Visualization

Visual process modeling

Halftones

Mathematical modeling

Rhodium

Gaussian filters

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