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    • 23. 发明授权
    • Halftone image generation method and image processing system and computer program product thereof
    • 半色调图像生成方法及图像处理系统及其计算机程序产品
    • US08390890B2
    • 2013-03-05
    • US12899245
    • 2010-10-06
    • Jing-Ming GuoYun-Fu Liu
    • Jing-Ming GuoYun-Fu Liu
    • H04N1/405G06K9/00
    • H04N1/4052
    • A halftone image generation method used in a system including an image input module and a halftoning processing module for generating a halftone image is disclosed. First, an original image is received by the image input module and a dot diffusion process is performed to the original image to generate the halftone image using a first class matrix with a first size and a corresponding first diffused weighting matrix with a first diffused area size, wherein the first class matrix indicates a processing order of the dot diffusion process and the first class matrix with the first size, the first diffused area size and the corresponding first diffused weighting matrix with the first diffused area size are optimized results determined in advance by the halftoning processing module according to class matrixes of different sizes and diffused areas of different sizes.
    • 公开了一种在包括用于产生半色调图像的图像输入模块和半色调处理模块的系统中使用的半色调图像生成方法。 首先,由图像输入模块接收原始图像,并且对原始图像执行点扩散处理,以使用具有第一尺寸的第一等级矩阵和具有第一扩散区域尺寸的相应的第一扩散加权矩阵来生成半色调图像 其中,所述第一类矩阵表示所述点扩散处理的处理顺序,具有第一大小的第一等级矩阵,第一扩散区域大小和具有第一扩散区域大小的对应的第一扩散加权矩阵是由 根据不同大小的类矩阵和不同大小的扩散区域的半色调处理模块。
    • 25. 发明申请
    • HALFTONE IMAGE GENERATION METHOD AND IMAGE PROCESSING SYSTEM AND COMPUTER PROGRAM PRODUCT THEREOF
    • HALFTONE图像生成方法和图像处理系统及其计算机程序产品
    • US20110142340A1
    • 2011-06-16
    • US12899245
    • 2010-10-06
    • Jing-Ming GUOYun-Fu LIU
    • Jing-Ming GUOYun-Fu LIU
    • G06K9/00
    • H04N1/4052
    • A halftone image generation method used in a system including an image input module and a halftoning processing module for generating a halftone image is disclosed. First, an original image is received by the image input module and a dot diffusion process is performed to the original image to generate the halftone image using a first class matrix with a first size and a corresponding first diffused weighting matrix with a first diffused area size, wherein the first class matrix indicates a processing order of the dot diffusion process and the first class matrix with the first size, the first diffused area size and the corresponding first diffused weighting matrix with the first diffused area size are optimized results determined in advance by the halftoning processing module according to class matrixes of different sizes and diffused areas of different sizes.
    • 公开了一种在包括用于产生半色调图像的图像输入模块和半色调处理模块的系统中使用的半色调图像生成方法。 首先,由图像输入模块接收原始图像,并且对原始图像执行点扩散处理,以使用具有第一尺寸的第一等级矩阵和具有第一扩散区域尺寸的相应的第一扩散加权矩阵来生成半色调图像 其中,所述第一类矩阵表示所述点扩散处理的处理顺序,具有第一大小的第一等级矩阵,第一扩散区域大小和具有第一扩散区域大小的对应的第一扩散加权矩阵是由 根据不同大小的类矩阵和不同大小的扩散区域的半色调处理模块。
    • 28. 发明申请
    • DIGITAL HALFTONING METHOD UTILIZING DIFFUSED WEIGHTING AND CLASS MATRIX OPTIMIZATION
    • 使用扩展加权和类矩阵优化的数字化方法
    • US20100033764A1
    • 2010-02-11
    • US12187546
    • 2008-08-07
    • Jing-ming GuoYun-fu Liu
    • Jing-ming GuoYun-fu Liu
    • H04N1/405
    • H04N1/4053
    • The present invention discloses a digital halftoning method. The method comprises steps of: (a1) dividing an original image into non-overlapping blocks; (a2) obtaining a Least-Mean-Square trained (LMS-trained) filter by comparing at least a training image and a halftone result corresponding to the training image (a3) optimizing a class matrix with the LMS-trained filter, which involves the diffused area and the diffused weightings; and (a4) processing the non-overlapping blocks by performing a dot diffusion procedure with the optimized class matrix and the diffused weightings to generate a halftone image corresponding to the original image. A detailed class matrix optimizing method as in the above-mentioned step (a3) is also disclosed.
    • 本发明公开了一种数字半色调方法。 该方法包括以下步骤:(a1)将原始图像划分成非重叠块; (a2)通过将至少训练图像和对应于训练图像(a3)的半色调结果进行比较来获得最小均方训练(LMS训练)滤波器,该训练图像(a3)与LMS训练的滤波器优化类矩阵,其涉及 扩散面积和扩散重量; 和(a4)通过利用优化的类矩阵和扩散加权执行点扩散过程来生成与原始图像相对应的半色调图像来处理非重叠块。 还公开了如上述步骤(a3)中的详细的类矩阵优化方法。