A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color2Gray: salience-preserving color removal
ACM SIGGRAPH 2005 Papers
Decolorize: Fast, contrast enhancing, color to grayscale conversion
Pattern Recognition
An improved contrast enhancing approach for color-to-grayscale mappings
The Visual Computer: International Journal of Computer Graphics
Robust color-to-gray via nonlinear global mapping
ACM SIGGRAPH Asia 2009 papers
Selecting discrete and continuous features based on neighborhood decision error minimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The Complete Guide to Black & White Digital Photography
The Complete Guide to Black & White Digital Photography
Color-to-gray conversion using ISOMAP
The Visual Computer: International Journal of Computer Graphics
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Image and video decolorization by fusion
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
A color to grayscale conversion considering local and global contrast
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Gaussian mixture model in improved HLS color space for human silhouette extraction
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
Enhancing by saliency-guided decolorization
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Detecting boundaries in a vector field
IEEE Transactions on Signal Processing
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
| Hi-index | 0.00 |
This paper presents a new color-to-gray conversion algorithm capturing the perceived appearance of color images. Based on the Filter Theory, we formulate a novel measurement of channel-level distinction, called Channel Salience, to depict the filter level of three color stimuli. This salience metric guides a contrast adjustment process to enhance the perceived grayscale in the final output with a two-steps conversion. Experimental results show that our algorithm produces pleasing results for a variety of color images and we further extend the Channel Salience to edge detection.