Dept. of Electr. Eng., Notre Dame Univ., IN.
IEEE Trans Image Process. 1997;6(4):574-83. doi: 10.1109/83.563322.
There has been a tremendous amount of research in the area of image halftoning, where the goal has been to find the most visually accurate representation given a limited palette of gray levels (often just two, black and white). This paper focuses on the inverse problem, that of finding efficient techniques for reconstructing high-quality continuous-tone images from their halftoned versions. The proposed algorithms are based on a maximum a posteriori (MAP) estimation criteria using a Markov random field (MRF) model for the prior image distribution. Image estimates obtained with the proposed model accurately reconstruct both the smooth regions of the image and the discontinuities along image edges. Algorithms are developed and example gray-level reconstructions are presented generated from both dithered and error-diffused halftone originals. Application of the technique to the problems of rescreening and the processing of halftone images are shown.
在图像半色调领域已经进行了大量的研究，其目标是在有限的灰度级调色板（通常只有两个，黑色和白色）中找到最视觉准确的表示。本文侧重于逆问题，即从半色调版本中找到高效技术来重建高质量的连续色调图像。所提出的算法基于最大后验（MAP）估计准则，并使用马尔可夫随机场（MRF）模型对先验图像分布进行建模。所提出的模型得到的图像估计值可以准确地重建图像的平滑区域和图像边缘的不连续性。开发了算法，并从抖动和误差扩散半色调原始图像生成了示例灰度级重建。展示了该技术在重网屏和处理半色调图像问题上的应用。
