Color image quantization for frame buffer display
SIGGRAPH '82 Proceedings of the 9th annual conference on Computer graphics and interactive techniques
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Color2Gray: salience-preserving color removal
ACM SIGGRAPH 2005 Papers
An Algebraic Approach to Surface Reconstruction from Gradient Fields
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Direct Methods for Sparse Linear Systems (Fundamentals of Algorithms 2)
Direct Methods for Sparse Linear Systems (Fundamentals of Algorithms 2)
Decolorize: Fast, contrast enhancing, color to grayscale conversion
Pattern Recognition
Robust color-to-gray via nonlinear global mapping
ACM SIGGRAPH Asia 2009 papers
What is the range of surface reconstructions from a gradient field?
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
An efficient perception-based adaptive color to gray transformation
Computational Aesthetics'07 Proceedings of the Third Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Real-time contrast preserving decolorization
SIGGRAPH Asia 2012 Technical Briefs
Grey conversion via perceived-contrast
The Visual Computer: International Journal of Computer Graphics
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For the conversion of a color image to a perceptually plausible grayscale one, the global and local contrast are simultaneously considered in this paper. The contrast is measured in terms of gradient field, and the energy function is designed to have less value when the gradient field of the grayscale image is closer to that of original color image (called target gradient field). For encoding both of local and global contrast into the energy function, the target gradient field is constructed from two kinds of edges : one that connects each pixel to neighboring pixels and the other that connects each pixel to predetermined landmark pixels. Although we can have exact solution to the energy minimization in the least squares sense, we also present a fast implementation for the conversion of large image, by approximating the energy function. The problem is then reduced to reconstructing a grayscale image from the modified gradient field over the standard 4-neighborhood system, and this can be easily solved by the fast 2D Poisson solver. In the experiments, the proposed method is tested on various images and shown to give perceptually more plausible results than the existing methods.