Title :
A general framework for low level vision
Author :
Sochen, Nir ; Kimmel, Ron ; Malladi, Ravikanth
fDate :
3/1/1998 12:00:00 AM
Abstract :
We introduce a new geometrical framework based on which natural flows for image scale space and enhancement are presented. We consider intensity images as surfaces in the (x,I) space. The image is, thereby, a two-dimensional (2-D) surface in three-dimensional (3-D) space for gray-level images, and 2-D surfaces in five dimensions for color images. The new formulation unifies many classical schemes and algorithms via a simple scaling of the intensity contrast, and results in new and efficient schemes. Extensions to multidimensional signals become natural and lead to powerful denoising and scale space algorithms
Keywords :
computer vision; edge detection; image colour analysis; image enhancement; image segmentation; smoothing methods; 2D surface; 3D space; color images; computer vision; denoising algorithms; geometrical framework; gray-level images; image enhancement; image flow; image scale space; image segmentation; image smoothing; intensity contrast scaling; intensity images; low level vision; multidimensional signals; nonlinear diffusion algorithm; scale space algorithms; Color; Computer vision; Detectors; Image edge detection; Image enhancement; Laboratories; Mathematics; Noise reduction; Physics; Two dimensional displays;
Journal_Title :
Image Processing, IEEE Transactions on
