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Color recovery of black-and-white halftoned images via categorized color-embedding look-up tables
Affiliation:1. ViRVIG, Computer Science Department, Universitat Politècnica de Catalunya, Jordi Girona 1-3, Barcelona, Spain;2. Computer Vision Center, Department of Computer Science, Universitat Autonòma de Barcelona, Edifici O, Bellaterra, Spain;1. Institute of Chinese Studies, Freie Universität Berlin, Fabeckstr. 23-25, 14195 Berlin, Germany;2. Institute of Economics and Finance, Nanjing Audit University, 211815 Nanjing, China
Abstract:A new method of recovering the original colors of black-and-white (B&W) halftoned images with homogeneous dot patterns is proposed. The conventional inverse halftoning method, which uses a look-up table (LUT), can establish the relation between the halftoned patterns and the corresponding gray levels, while the conventional reversible color to gray conversion method can recover the original colors from a given color-embedded gray image. To accomplish our goal of original color recovery from B&W halftoned patterns, an approach of combining the conventional inverse halftoning and reversible color to gray conversion is presented in this paper. Differently from the conventional method of inverse halftoning via LUT, four LUTs categorized according to the red, green, blue, and gray reference colors are designed to more accurately map a specific B&W halftone pattern into the corresponding color-embedded gray level based on the observation that the shapes of the halftone patterns depend on input colors, thereby increasing the color recovery accuracy. Also, a color mapping method based on a linear regression which models the relation between the recovered colors and the original colors is introduced to adjust the initially recovered colors more closely to the original colors. Experimental results show that unknown original colors can be recovered from B&W halftoned images via the proposed method.
Keywords:Color recovery  Halftone patterns  Look-up table  Color to gray conversion  Colorization
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