打印机光谱特性化方法研究综述

目的 打印输出技术是目前国内外图像复制领域的主流技术。打印机特征化旨在建立打印机输入控制值与输出色彩信息值之间的对应关系，保证打印输出图像各像素色彩值的准确性。基于可见光谱的打印机特性化过程，以图像光谱信息作为打印机特性化过程中的色彩控制依据，可避免基于色度的打印输出过程所固有的同色异谱问题，实现图像色彩复制领域最高级别的无条件颜色匹配。在广泛文献调研的基础上，本文回顾了打印机光谱特性化方法各部分研究的发展历程，分析介绍了该领域主要研究内容及其研究现状，对打印机光谱特性化方法流程进行了较为全面的综述。方法 以Yule-Nielsen修正的光谱Neugebauer模型（YNSN模型）为典型代表，从打印机墨量限制方法、正向光谱预测模型、反向光谱分色模型以及色彩匹配评价度量4个方面，对目前基于可见光谱的打印机特性化方法研究情况进行了总结与归纳，并结合现有研究存在的问题对未来研究发展趋势进行了展望。结果 综合近几年该领域研究发展情况，认为目前打印机光谱特性化方法研究在墨量限制算法合理性、正反向建模精度等方面已经取得了较为理想的结果。然而，尽管已有20多年的广泛研究，鉴于光谱数据的高维性以及具体应用场景的多样性，导致准确而高效的实现光谱打印机特性化仍然是一个极具难度的问题，特别在建模效率提高、模型适用性增强、模型物理意义提升以及评价度量综合性能优化等方面，目前研究仍存在较大的研究发展空间。结论 打印机光谱特性化是实现图像色彩信息高保真打印复制的必要手段，其今后将继续在图像复制领域起到非常关键作用。然而，由于基于光谱的打印机特性化过程涉及光谱学及色度学理论、半色调呈色理论、最优化计算理论、人眼视觉机理、数字加网技术等多种理论与技术，故其研究具有一定的难度与挑战性。本文对打印机光谱特性化方法研究现状进行了较为深入的介绍与分析，意在使国内同行对该领域有一个较为全面的了解，以期引起更多研究者对该领域的关注。由于篇幅所限，许多问题未及深究。

Review of spectral printer characterization

Objective Until recently, printing technology has been a kind of mainstream technology for color image reproduction. Printer characterization aims at establishing the relationship between the input control values of the printer and its output colors. It is the core of color accuracy controlling for each image pixel during the printing process. Spectral-based printer characterization conquers the metamerism problem of colorimetric characterization and thus can achieve unconditional matched color reproduction, which represents the highest level of color reproduction in the state of the art. Based on the extensive and in-depth investigation of existing articles, in this paper we review the research development of the main topics of spectral-based printer characterization and present a comprehensive survey of various existing methods, with more than 60 related reviewed pieces of literature. Method This review employs the famous Yule-Nielsen modified spectral Neugebauer model as an example; critically reviews the research of spectral-based printer characterization from the aspects of ink limitation algorithm development, spectral prediction model establishment, spectral separation method development, and image color match evaluation metric optimization; and discusses future research trends according to the existing problems of the current study. Result Based on the comprehensive survey of the current research situation, significant progress has been made in the field of ink limitation algorithm development, spectral prediction modeling, and spectral separation algorithm development. However, in spite of more than 20 years of research and development in this field, the general problem of how to precisely and efficiently conduct spectral-based printer characterization still exists, not only because of the high dimensionality of spectral data but also because of the variety of actual applications. Therefore, in many aspects, such as improving modeling efficiency, enhancing model applicability, interpreting the model's physical meaning, and optimizing evaluation metrics, further work is still needed. Conclusion Spectral-based printer characterization is an essential means for high-fidelity color reproduction and will continue to play an important role in the image reproduction workflow. However, because of its interdisciplinarity among several subjects, which involve spectroscopy and colorimetry theory, halftone color rendering theory, optimization theory, human vision theory, and digital halftoning technology, difficulties surely exist. This paper introduces the main topics and analyzes the current research situation of spectral-based printer characterization. This overview aims to help researchers in this area to have a more intuitive understanding of existing spectral-based printer characterization methods and to attract more researchers' attention in this field. Given the space limitation, some issues are not discussed in detail.