Line Integral Convolution for Visualization of Fiber Tract Maps from DTI
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
A Geometric Functional for Derivatives Approximation
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Geometric-Variational Approach for Color Image Enhancement and Segmentation
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Journal of Mathematical Imaging and Vision
Differential Equations for Morphological Amoebas
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Morphological Amoebas Are Self-snakes
Journal of Mathematical Imaging and Vision
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
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A general geometrical framework for image processing is presented. We consider intensity images as surfaces in the (x, I) space. The image is thereby a two dimensional surface in three dimensional space for gray level images. The new formulation unifies many classical schemes, algorithms, and measures via choices of parameters in "master" geometrical measure. More important, it is a simple and efficient tool for the design of natural schemes for image enhancement, segmentation, and scale space. Here we give the basic motivation and apply the scheme to enhance images. We present the concept of an image as a surface in dimensions higher than the three dimensional intuitive space. This will help us handle movies, color, and volumetric medical images.