Structure-Aware Error Diffusion - Archive ouverte HAL
Article Dans Une Revue ACM Transactions on Graphics Année : 2009

Structure-Aware Error Diffusion

Résumé

We present an original error-diffusion method which produces visually pleasant halftone images while preserving fine details and visually identifiable structures present in the original images. Our method is conceptually simple and computationally efficient. The source image is analyzed, and its local frequency content is detected. The main component of the frequency content (main frequency, orientation and contrast) serve as lookup table indices to a pre-calculated database of modifications to a standard error diffusion. The modifications comprise threshold modulation and variation of error-diffusion coefficients. The whole system is calibrated in such a way that the produced halftone images are visually close to the original images (patches of constant intensity, patches containing sinusoidal waves of different frequencies/orientations/contrasts, as well as natural images of different origins). Our system produces images of visual quality comparable to that presented in [Pang et al. 2008], but much faster. When processing typical images of linear size of several hundreds of pixels, our error-diffusion system is two to three orders of magnitude faster than [Pang et al. 2008]. Thanks to its speed combined with high visual quality, our error-diffusion algorithm can be used in many practical applications which may require digital halftoning: printing, visualization, geometry processing, various sampling techniques, etc.
Fichier principal
Vignette du fichier
Liris-4442.pdf (1.87 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01437787 , version 1 (06-03-2017)

Licence

Identifiants

  • HAL Id : hal-01437787 , version 1

Citer

Jianghao Chang, Benoit Alain, Victor Ostromoukhov. Structure-Aware Error Diffusion. ACM Transactions on Graphics, 2009, 5, 28, pp.162:1-162:8. ⟨hal-01437787⟩
442 Consultations
358 Téléchargements

Partager

More