Mathematical Analysis of a Inf-Convolution Model for Image Processing

M. Bergounioux ()
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M. Bergounioux: Université d’Orléans

Journal of Optimization Theory and Applications, 2016, vol. 168, issue 1, No 1, 21 pages

Abstract: Abstract We deal with a second-order image decomposition model to perform denoising and texture extraction that was previously presented. We look for the decomposition of an image as the summation of three different order terms. For highly textured images, the model gives a two-scale texture decomposition: The first-order term can be viewed as a macro-texture (larger scale) which oscillations are not too large, and the zero-order term is the micro-texture (very oscillating) that contains the noise. Here, we perform mathematical analysis of the model and give qualitative properties of solutions using the dual problem and inf-convolution formulation.

Keywords: Second-order total variation; Image decomposition; Variational method; Inf-convolution; 65D18; 68U10; 65K10 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10957-015-0734-8

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