A Tensor Variational Formulation of Gradient Energy Total Variation
2015 (English)In: ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, EMMCVPR 2015, Springer Berlin/Heidelberg, 2015, Vol. 8932, 307-320 p.Conference paper (Refereed)
We present a novel variational approach to a tensor-based total variation formulation which is called gradient energy total variation, GETV. We introduce the gradient energy tensor into the GETV and show that the corresponding Euler-Lagrange (E-L) equation is a tensor-based partial differential equation of total variation type. Furthermore, we give a proof which shows that GETV is a convex functional. This approach, in contrast to the commonly used structure tensor, enables a formal derivation of the corresponding E-L equation. Experimental results suggest that GETV compares favourably to other state of the art variational denoising methods such as extended anisotropic diffusion (EAD) and total variation (TV) for gray-scale and colour images.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2015. Vol. 8932, 307-320 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online)
IdentifiersURN: urn:nbn:se:liu:diva-112270DOI: 10.1007/978-3-319-14612-6_23ISI: 000357502000023ISBN: 978-3-319-14612-6ISBN: 978-3-319-14611-9OAI: oai:DiVA.org:liu-112270DiVA: diva2:764721
10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2015), 13-16 January 2015, Hong Kong, China