Journal of Inverse and Ill-posed Problems
Editor-in-Chief: Kabanikhin, Sergey I.
6 Issues per year
IMPACT FACTOR increased in 2015: 0.987
Rank 59 out of 312 in category Mathematics and 93 out of 254 in Applied Mathematics in the 2015 Thomson Reuters Journal Citation Report/Science Edition
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Source Normalized Impact per Paper (SNIP) 2015: 1.106
Impact per Publication (IPP) 2015: 0.712
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Motion estimation by hybrid diffusion: theory and implementation
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.