Digital Color Halftoning
Transferring color to greyscale images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Colorization using optimization
ACM SIGGRAPH 2004 Papers
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Fast and adaptive color-to-grayscale conversion
ACM SIGGRAPH 2006 Sketches
Reversible color-to-gray mapping using subband domain texturization
Pattern Recognition Letters
An efficient median filter based method for removing random-valued impulse noise
Digital Signal Processing
Accurate reversible color-to-gray mapping algorithm without distortion conditions
Pattern Recognition Letters
Look-up table (LUT) method for inverse halftoning
IEEE Transactions on Image Processing
Color to gray and back: color embedding into textured gray images
IEEE Transactions on Image Processing
Improved bilateral filter for suppressing mixed noise in color images
Digital Signal Processing
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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.