Adaptive diffusion constrained total variation scheme with application to `cartoon + texture + edge' image decomposition
Juan C. Moreno*, V. B. Surya Prasath$^, D. Vorotnikov#, Hugo Proença*, K. Palaniappan$
*IT-Instituto de Telecomunicações, Department of Computer Science, University of Beira Interior, Portugal
#Department of Mathematics, University of Coimbra, Portugal
$Computational Imaging and Visualization Analysis Lab, Department of Computer Science, University of Missouri-Columbia, USA
We consider an image decomposition model involving a variational (minimization) problem and an evolutionary partial differential equation (PDE). We utilize a linear inhomogenuous diffusion constrained and weighted total variation (TV) scheme for image adaptive decomposition. An adaptive weight along with TV regularization splits a given image into three components representing the geometrical (cartoon), textural (small scale - microtextures), and edges (big scale - macrotextures). We study the wellposedness of the coupled variational-PDE scheme along with an efficient numerical scheme based on Chambolle's dual minimization. We provide extensive experimental results in cartoon-texture-edges decomposition, and denoising as well compare with other related variational, coupled anisotropic diffusion PDE based methods.
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J. C. Moreno, V. B. S. Prasath, D. Vorotnikov, H. Proenca, K. Palaniappan. Adaptive diffusion constrained total variation scheme with application to `cartoon + texture + edge' image decomposition. Submitted
This work was done while the author was at the IPAM
, University of California Los Angeles, CA, USA. The author thanks the IPAM institute for their great hospitality and support during the visit.