The reduction of a structural pattern at specific gray levels or at the special condition of image data has mainly been discussed in digital halftone methods. This problem is more severe in some flat panel displays because their black levels typically are brighter than other displays blocks. The authors proposed an advanced confined error diffusion (ACED) algorithm which was a well-organized halftone algorithm for flat panel devices. In this paper, we extend the ACED algorithm to the multi-level systems, which are capable of displaying more than 2 levels. Our extension has two merits for the hardware implementation. First, it can be processed in real time using the look-up table based method. The second one is the flexibility of selecting the used gray level. This paper discusses the performance of the proposed algorithms with experimental results for natural test images.

This paper proposes a new color halftone image quality assessment method based upon the color structural similarity measure with considering the human visual characteristics. To include the color visual characteristics, we carry out the color filtering for each luminance, red-green, and blue-yellow channels. Then, we apply the color structural similarity measure to the color filtered images, which are the reference image and the halftoned image, to evaluate the localized structural difference. By considering those characteristics, in this paper, the assessment of the color halftone images can be realized. We apply the proposed measure to the various kinds of color halftone images and confirm that the proposed measure can give reasonable results compared with the results by subjective evaluation.