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Journal of Inverse and Ill-posed Problems

Editor-in-Chief: Kabanikhin, Sergey I.

6 Issues per year

IMPACT FACTOR increased in 2014: 0.880
Rank 74 out of 310 in category Mathematics and 113 out of 255 in Applied Mathematics in the 2014 Thomson Reuters Journal Citation Report/Science Edition

SCImago Journal Rank (SJR) 2014: 0.516
Source Normalized Impact per Paper (SNIP) 2014: 1.430
Impact per Publication (IPP) 2014: 0.613

Mathematical Citation Quotient (MCQ) 2014: 0.51



Motion estimation by hybrid diffusion: theory and implementation

L. X. Yang / D. N. Hào / H. Sahli

ETRO/IRIS, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussel, Belgium. E-mails: , ,

Citation Information: Journal of Inverse and Ill-posed Problems jiip. Volume 14, Issue 3, Pages 307–330, ISSN (Online) 1569-3953, ISSN (Print) 0928-0219, DOI: 10.1515/156939406777340900,

Publication History

Published Online:

2D motion field is the velocity field which presents the apparent motion from one image to another one in an image sequence. It provides important motion information and is widely used in image processing and computer vision. In this paper, with the objective of accurate estimation of a 2D dense motion field, a hybrid diffusion model is proposed. The present approach differs from those in the literature in the sense that the diffusion model and its associated objective functional are driven by both the flow field and image, through a nonlinear isotropic diffusion term and a linear anisotropic diffusion term, respectively. The diffusion function in the model is required to be non increasing, non negative, differentiable and bounded. Using Schauder's fixed point theorem, we prove the existence, stability and uniqueness of the solution to the proposed hybrid diffusion model. A semi-implicit finite difference scheme is proposed to implement the hybrid diffusion model. We demonstrate its efficiency and accuracy by experiments on both synthetic and real image sequences.

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