Near-optimal model-based halftoning technique with dot gain

Sasan Gooran; Bjoern Kruse

doi:10.1117/12.302433

1 April 1998 Near-optimal model-based halftoning technique with dot gain

Sasan Gooran, Bjoern Kruse

Proceedings Volume 3308, Very High Resolution and Quality Imaging III; (1998) https://doi.org/10.1117/12.302433
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

We present a novel halftoning technique for transformation of continuous tone images into binary halftoned separations. The algorithm is based on a successive assessment of the near optimum sequence of positions to render. The impact of each rendered point is fed back to the process as a distribution function thereby influencing the following evaluations. The distribution function is not constant over the density range. In order to be able to separate the dots adequately in the highlights the 'width or radius' of the distribution has to be made larger than in the mid-tones. The human visual system and the effect of dot gain are also taken into account in this algorithm. The notion of incremental dot gain is introduced. Since the series of positions to render are not known in advance the final necessary dot gain compensation is impossible to assess. However the incremental dot gain can be computed in advance for each configuration of dots and taken into account in the process of generating the output. Some aspects of the process have certain resemblance with error distribution based algorithms. However the raster scanning sequence of rendering the output points in usual error diffusion algorithms is completely different from the image dependent traversal described in this paper.

Citation Download Citation

Sasan Gooran and Bjoern Kruse "Near-optimal model-based halftoning technique with dot gain", Proc. SPIE 3308, Very High Resolution and Quality Imaging III, (1 April 1998); https://doi.org/10.1117/12.302433

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available