A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Image Processing - Principles and Applications
Image Processing - Principles and Applications
Performance Analysis of Color Image Watermarking Schemes Using Perceptually Redundant Signal Spaces
IIH-MSP '06 Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia
A Perceptual Color Edge Detection Algorithm
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
Color-edge detection based on discrimination of noticeable color contrasts
International Journal of Imaging Systems and Technology
Robust color edge detection through tensor voting
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Color quantization and processing by Fibonacci lattices
IEEE Transactions on Image Processing
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Many grayscale image processing techniques such as edge and feature detection, template matching, require the computations of image gradients and intensity difference. These computations in grayscale are very much like measuring color difference between two colors. The goal of this work is to determine an efficient method to represent color difference so that many existing grayscale image processing techniques that require the computations of intensity difference and image gradients can be adapted for color without significantly increasing the amount of data to process and without significantly altering the grayscale-based algorithms. In this paper, several perceptual color contrast measurement formulas are evaluated to determine the most applicable metric for color difference representation. Well-known edge and feature detection algorithms using color contrast are implemented to prove its feasibility.