Title :
Feature-preserving flows: a stochastic differential equation´s view
Author :
Unal, Gozde B. ; Krim, Hamid ; Yezzi, Anthony
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
Abstract :
Evolution equations have proven to be useful in tracking fine to coarse features in a single level curve and/or in an image. We give a stochastic insight to a specific evolution equation, namely the geometric heat equation, and subsequently use this insight to develop a class of feature-driven diffusions. A progressive smoothing along desired features of a level curve is aimed at overcoming effects of noisy environment during feature extraction and denoising applications
Keywords :
feature extraction; image restoration; noise; partial differential equations; smoothing methods; stochastic processes; tracking; evolution equations; feature extraction; feature-driven diffusion; feature-preserving flows; geometric heat equation; image denoising; image features tracking; image restoration; noisy environment; partial differential equation; progressive smoothing; single level curve; stochastic differential equation; Computer vision; Differential equations; Feature extraction; Filters; Level set; Noise reduction; Smoothing methods; Stochastic processes; Target tracking; Working environment noise;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.901104
