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Martin Burger Institut für Numerische und Angewandte Mathematik Total Variation and Related Methods II

Martin Burger Institut für Numerische und Angewandte Mathematik European Institute for Molecular Imaging CeNoS Total Variation and Related Methods II

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Martin Burger Institut für Numerische und Angewandte Mathematik

European Institute for Molecular Imaging CeNoS

Total Variation and Related Methods II

Total Variation 2

Cetraro, September 2008Martin Burger

Variational Methods and their Analysis We investigate the analysis of variational methods in imagingMost general form:

Total Variation 3

Cetraro, September 2008Martin Burger

Variational Methods and their Analysis Questions:- Existence- Uniqueness- Optimality conditions for solutions (-> numerical methods)- Structural properties of solutions- Asymptotic behaviour with respect to

Total Variation 4

Cetraro, September 2008Martin Burger

Variational Methods and their Analysis Two simplifying assumptions:

-Noise is Gaussian (variance can be incorporated into )

- A is linear ´

Y Hilbert space

Total Variation 5

Cetraro, September 2008Martin Burger

TV Regularization Under the above assumptions we have

Total Variation 6

Cetraro, September 2008Martin Burger

Mean Value Technical simplification by eliminating mean value

Total Variation 7

Cetraro, September 2008Martin Burger

Mean Value Eliminate mean value

Hence, minimum is attained among those functions with mean value c

Total Variation 8

Cetraro, September 2008Martin Burger

Mean Value We can minimize a-priori over the mean value and restrict the image to mean value zeroW.r.o.g.

Total Variation 9

Cetraro, September 2008Martin Burger

Structure of BV0 Equivalent norm

Total Variation 10

Cetraro, September 2008Martin Burger

Poincare-InequalityProof. Assume

does not hold. Then for each natural number n there is such that

Total Variation 11

Cetraro, September 2008Martin Burger

Poincare-InequalityProof (ctd).

Total Variation 12

Cetraro, September 2008Martin Burger

Poincare-InequalityProof (ctd).

Total Variation 13

Cetraro, September 2008Martin Burger

Dual Space Property Define

Total Variation 14

Cetraro, September 2008Martin Burger

Dual Space Property

Total Variation 15

Cetraro, September 2008Martin Burger

Dual Space Property

Total Variation 16

Cetraro, September 2008Martin Burger

Dual Space Property

Total Variation 17

Cetraro, September 2008Martin Burger

Dual Space Property

Total Variation 18

Cetraro, September 2008Martin Burger

Existence Basic ingredients of an existence proof are-Sequential lower semicontinuity

- Compactness

Total Variation 19

Cetraro, September 2008Martin Burger

Existence What is the correct topology ?

Total Variation 20

Cetraro, September 2008Martin Burger

Lower SemicontinuityCompactness follows in the weak* topology.Lower semicontinuity ?

Total Variation 21

Cetraro, September 2008Martin Burger

Lower Semicontinuity

Total Variation 22

Cetraro, September 2008Martin Burger

Lower Semicontinuity

Total Variation 23

Cetraro, September 2008Martin Burger

Lower Semicontinuity First term:

analogous proof implies

Total Variation 24

Cetraro, September 2008Martin Burger

Existence Theorem: Let J be sequentially lower semicontinuous and

be compact. Then there exists a minimum of JProof.

Total Variation 25

Cetraro, September 2008Martin Burger

Existence Proof (ctd). Due to compactness, there exists a subsequence, again denoted by such that

By lower semicontinuity

Hence, u is a minimizer

Total Variation 26

Cetraro, September 2008Martin Burger

Uniqueness Since the total variation is not strictly convex and definitely will not enforce uniqueness, the data term should do

Proof: