1991
DOI: 10.1109/21.101134
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Design of minimum visual modulation halftone patterns

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Cited by 131 publications
(91 citation statements)
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“…Most model-based halftoning methods use variants of this distortion measure. For the spatial response of the eye, however, a number of other models have also been proposed, including some that take into account known anisotropy in the visual-system [292].…”
Section: B Halftoningmentioning
confidence: 99%
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“…Most model-based halftoning methods use variants of this distortion measure. For the spatial response of the eye, however, a number of other models have also been proposed, including some that take into account known anisotropy in the visual-system [292].…”
Section: B Halftoningmentioning
confidence: 99%
“…For display of gray-scale images on binary output devices, a number of researchers have suggested iterative schemes that provide good solutions with varying computational requirements [292]- [296]. For color displays with reasonable sized palettes, the problem remains computationally infeasible at present.…”
Section: B Halftoningmentioning
confidence: 99%
“…Different spatial HVS models have been tested for use in image halftoning algorithms [23]- [29]. The performance of different HVS models [30]- [33] was evaluated for direct binary search (DBS) based halftoning in [34], and it was found that Nasanen's model, which gives a low-pass approximation, produced halftones with the best subjective quality.…”
Section: Human Visual System Modelmentioning
confidence: 99%
“…Similar to the algorithm of Section III-A, T 0 still controls the amount of (spatial) perceptual error introduced in frame DE i during the process of DWE reduction. If the trial change is accepted, then E i,de,c,total is updated as: (23) Note that the update suggested in (23) needs to be done everytime a pixel value is changed in the i th enhanced frame, DE i . This update ensures that, at any moment,Ē i,de,c,total reflects the actual perceptual error of the enhanced frame DE i due to all pixel changes that have taken place thus far.…”
Section: B Algorithm Ii: Computationally Efficient Reduction Of Dirtmentioning
confidence: 99%
“…In 1974, Mannos and Sakrison established the HVS model for the first time [28]. Numerous researchers have been conducting studies on the HVS [29], [30].…”
Section: Uman Visual System (Hvs) In Watermarkingmentioning
confidence: 99%