Total Variation Minimization for Scalar/Vector Regularization
Dibos, Françoise; Koepfler, Georges; Monasse, Pascal (2003), Total Variation Minimization for Scalar/Vector Regularization, in Osher, Stanley; Paragios, Nikos, Geometric Level Set Methods in Imaging, Vision, and Graphics, Springer : Berlin, p. 121-140. http://dx.doi.org/10.1007/0-387-21810-6_7
Book titleGeometric Level Set Methods in Imaging, Vision, and Graphics
Book authorOsher, Stanley; Paragios, Nikos
Number of pages513
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Abstract (EN)In this chapter we present regularization by using Total Variation (TV) minimization based on a level set approach. After introducing the problem of regularization and citing related work, we introduce our main tool, the Fast Level Sets Transform (FLST). This algorithm decomposes an image in a tree of shapes which gives us a non-redundant and complete representation of the image. This representation, associated to some theoretical facts about functions of bounded variation, leads us to a TV minimization algorithm based on level sets. We conclude by comparing this approach to other implementation and/or other models and show applications to regularization of gray scale and color images, as well as optical flow.
Subjects / KeywordsFast Level Sets Transform (FLST); level sets; Total Variation (TV) minimization
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