Color Characterization and Balancing by a Nonlinear Line Attractor Network for Image Enhancement
Neural Processing Letters
Natural color image enhancement and evaluation algorithm based on human visual system
Computer Vision and Image Understanding
Color image histogram equalization by absolute discounting back-off
Computer Vision and Image Understanding
Contrast enhancement of color images based on Wavelet Transform and human visual system
GVE '07 Proceedings of the IASTED International Conference on Graphics and Visualization in Engineering
Efficient multi-scale retinex algorithm using multi-rate image processing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptive color image enhancement based geometric mean filter
Proceedings of the 2011 International Conference on Communication, Computing & Security
Color compensation using nonlinear luminance-RGB component curve of a camera
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
High dynamic range optimal fuzzy color image enhancement using Artificial Ant Colony System
Applied Soft Computing
Pattern Recognition and Image Analysis
Image-Enhanced capsule endoscopy preserving the original color tones
MICCAI'11 Proceedings of the Third international conference on Abdominal Imaging: computational and Clinical Applications
Contrast brushes: interactive image enhancement by direct manipulation
Computational Aesthetics'09 Proceedings of the Fifth Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Quality enhancement of direct volume rendered images
VG'07 Proceedings of the Sixth Eurographics / Ieee VGTC conference on Volume Graphics
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The first step in many techniques for processing intensity and saturation in color images keeping hue unaltered is the transformation of the image data from RGB space to other color spaces such as LHS, HSI, YIQ, HSV, etc. Transforming from one space to another and processing in these spaces usually generate a gamut problem, i.e., the values of the variables may not be in their respective intervals. We study enhancement techniques for color images theoretically in a generalized setup. A principle is suggested to make the transformations gamut-problem free. Using the same principle, a class of hue-preserving, contrast-enhancing transformations is proposed; they generalize existing grey scale contrast intensification techniques to color images. These transformations are also seen to bypass the above mentioned color coordinate transformations for image enhancement. The developed principle is used to generalize the histogram equalization scheme for grey scale images to color images.