Many new proposals are continually published in the halftoning domain. Alas, the demonstration of the interest of the
proposed methods is often limited to a few favourable tests for the proposed methods, and images showing the defects of
the other halftoning methods.
The halftoning community needs to be able to compare a halftoning method with the innovations that appear in this
domain. A complete and measured evaluation of quality is necessary through to a well defined set of test images and
metrics to evaluate the algorithm.
This paper proposes a protocol for the quality assessment of digital halftoning algorithm that can be used to compare one
algorithm to another.
It discusses the assessment of halftoner quality. It analyzes the perceived image quality concepts and defines the
technical criteria that a good halftoner must match. A first sketch of a simple quality assessment protocol is proposed. It
is composed of test images and quality metrics.
This protocol could be used to provide new proposed halftoning algorithms with objective results.
There are two main families among the halftoning methods: halftoning by masking (i.e. blue noise masking) and error diffusion halftoning. The first family produces neither "worms" nor defects related to stationary regimes but has a limited spatial bandwidth. The error diffusion halftoning method is characterized by a very broad spatial bandwidth allowing good rendition of very thin lines and patterns but this method presents sometimes unpleasant worms or stationary regimes. These methods are complementary with respect to quality. In this paper we propose a halftoning algorithm in black and white, derived from the error diffusion of Floyd Steinberg. By using a new threshold modulation, our new method combines the advantages of both masking and error diffusion algorithms. In order to evaluate our algorithm we defined a set of test images allowing the evaluation of the critical points of quality for the technical imagery: graininess, patterning and spatial bandwidth. The rendering of the presented algorithm has low graininess, no unpleasant patterning and broad spatial bandwidth.