Approximating Non-linear Diffusion
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Approximating Non-linear Diffusion. / Dam, Erik B.; Olsen, Ole Fogh; Nielsen, Mads.
Scale Space Methods in Computer Vision: 4th International Conference, Scale Space 2003 Isle of Skye, UK, June 10–12, 2003 Proceedings. <Forlag uden navn>, 2003. p. 117-131 (Lecture notes in computer science, Vol. 2695/2003).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Approximating Non-linear Diffusion
AU - Dam, Erik B.
AU - Olsen, Ole Fogh
AU - Nielsen, Mads
N1 - Conference code: 4
PY - 2003
Y1 - 2003
N2 - We assess the feasibility of approximating non-linear diffusion processes with simple local Gaussian filters. The purpose of doing this is twofold. Firstly, the theoretical implications are by themselves interesting. Secondly, a successful method would reduce the need for computationally expensive implementations of non-linear diffusion schemes. We evaluate using isotropic and affine Gaussian filters for the task of approximating the local diffusion for a number of non-linear diffusion schemes. The approximations are firstly explored using an information theoretical approach and secondly evaluated based on their performance on a multi-scale segmentation application. The results show that while the approximations do not perform quite as well as the original non-linear scheme, the decrease in performance is acceptable for the evaluated task. Furthermore, the affine approximations perform significantly better than the isotropic.
AB - We assess the feasibility of approximating non-linear diffusion processes with simple local Gaussian filters. The purpose of doing this is twofold. Firstly, the theoretical implications are by themselves interesting. Secondly, a successful method would reduce the need for computationally expensive implementations of non-linear diffusion schemes. We evaluate using isotropic and affine Gaussian filters for the task of approximating the local diffusion for a number of non-linear diffusion schemes. The approximations are firstly explored using an information theoretical approach and secondly evaluated based on their performance on a multi-scale segmentation application. The results show that while the approximations do not perform quite as well as the original non-linear scheme, the decrease in performance is acceptable for the evaluated task. Furthermore, the affine approximations perform significantly better than the isotropic.
U2 - 10.1007/3-540-44935-3_9
DO - 10.1007/3-540-44935-3_9
M3 - Article in proceedings
SN - 978-3-540-40368-5
T3 - Lecture notes in computer science
SP - 117
EP - 131
BT - Scale Space Methods in Computer Vision
PB - <Forlag uden navn>
Y2 - 29 November 2010
ER -
ID: 5555912