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Monday, August 20, 2012

The coarea formula for BV functions

Today, we will discuss the coarea formula for BV functions, established by Fleming and Rishel in 1960 (W. Fleming, R. Rishel, An integral formula for total gradient variation, Arch. Math. 11 (1960), 218-222.)

Let us first recall the lower semicontinuity property of the total variation with respect to the strong convergence in L1(Ω):
Let {un}nΩ be a sequence in BV(Ω) strongly converging to some u in L1(Ω) and satisfying |un|BV<. Then uBV(Ω) and |u|BV(Ω)lim The coarea formula is as stated as follows:

Coarea formula: Let u be a given function in BV(\Omega). Then for almost every t in \mathbb{R}, the level set E_t=\{ x\in \Omega \subset \mathbb{R}^N: u(x) > t\} of u is a set of finite perimeter in \Omega, and
\begin{align} &Du=\int_{-\infty}^{\infty} D\chi_{E_t}\, dt,\\ &|u|_{BV(\Omega)}=|Du|(\Omega)=\int_{-\infty}^{\infty} \int_{\Omega}|D\chi_{E_t}|\, dt. \end{align}
The second assertion above is often written in terms of the perimeter of level sets as follows:
\begin{align} |u|_{BV(\Omega)}=\int_{-\infty}^{\infty} Per(E_t, \Omega) dt, \end{align}
where Per(E_t, \Omega)=\mathcal{H}^{N-1}(\Omega \cap \partial E_t) is the perimeter of the level set E_t.

Proof of the coarea formula: We follow the treatment of Variational Analysis in Sobolev and BV spaces by Attouch et al.

Part I: Proof of |Du|(\Omega) \leq \int_{-\infty}^{\infty}\int_{\Omega}|D\chi_{E_t}|\, dt:

Let us assume that D\chi_{E_t} belongs to \mathbf{M}(\Omega, \mathbb{R}^N), the set of all \mathbb{R}^N- valued Borel measures which is the set of all the \sigma- additive set functions \mu:\mathcal{B}(\Omega)\rightarrow \mathbb{R}^N, with \mu(\emptyset)=0. For all t in \mathbb{R} set
\begin{equation} f_t=\left\{ \begin{array}{ll} \chi_{E_t} & \mbox{if } t \geq 0 \\ -\chi_{\Omega \backslash E_t} & \mbox{if } t < 0 \end{array} \right. \end{equation} It is easy to see that u(x)=\int_{-\infty}^{\infty}f_t(x)\,dt for all x\in \Omega. For all \bar{\phi} \in C_c^1(\Omega, \mathbb{R}^N) we have \begin{align*} &\langle Du, \bar{\phi} \rangle \\ &= -\int_{\Omega} u \, \mbox{div} \,\bar{\phi} \, dx \\ & = - \int_{\Omega} \int_{-\infty}^{\infty} f_t \, \mbox{div} \,\bar{\phi} \, dt\,dx\\ &= - \int_{\Omega} \int_{-\infty}^{0} f_t \, \mbox{div} \,\bar{\phi} \, dt\,dx -\int_{\Omega} \int_{0}^{\infty} f_t \, \mbox{div} \,\bar{\phi} \, dt\,dx \\ &= \int_{\Omega} \int_{-\infty}^{0} \chi_{\Omega \backslash E_t} \, \mbox{div} \,\bar{\phi} \, dt\,dx -\int_{\Omega} \int_{0}^{\infty} \chi_{E_t} \, \mbox{div} \,\bar{\phi} \, dt\,dx \\ &=\int_{\Omega} \int_{-\infty}^{0} (1-\chi_{E_t}) \, \mbox{div} \,\bar{\phi} \, dt\,dx -\int_{\Omega} \int_{0}^{\infty} \chi_{E_t} \, \mbox{div} \,\bar{\phi} \, dt\,dx \\ &=\int_{\Omega} \int_{-\infty}^{0} \mbox{div} \,\bar{\phi} \, dt\,dx - \int_{\Omega} \int_{-\infty}^{0} \chi_{E_t} \, \mbox{div} \,\bar{\phi} \, dt\,dx-\int_{\Omega} \int_{0}^{\infty} \chi_{E_t} \, \mbox{div} \,\bar{\phi} \, dt\,dx \\ &= \int_{\Omega} \int_{-\infty}^{0} \mbox{div} \,\bar{\phi} \, dt\,dx-\int_{\Omega} \int_{-\infty}^{\infty} \chi_{E_t} \, \mbox{div} \,\bar{\phi} \, dt\,dx \\ &= 0-\int_{\Omega} \int_{-\infty}^{\infty} \chi_{E_t} \, \mbox{div} \,\bar{\phi} \, dt\,dx \\ &= \int_{-\infty}^{\infty} \langle D\chi_{E_t}, \bar{\phi}\rangle \,dt \end{align*} Hence, Du=\int_{-\infty}^{\infty} D\chi_{E_t}\, dt, and |Du|(\Omega) \leq \int_{-\infty}^{\infty}\int_{\Omega}|D\chi_{E_t}|\, dx dt.

Part II: (coverse) Proof of \int_{-\infty}^{\infty}\int_{\Omega}|D\chi_{E_t}|\, dxdt\leq |Du|(\Omega) :


Step i. We first assume that u belongs to the space \mathcal{A}(\Omega) of piecewise linear and continuous functions in \Omega. By linearity, one can assume that u=a\cdot x+b with a\in \mathbb{R}^N and b\in \mathbb{R}, so that

\begin{align*} &\int_{\Omega} |D\chi_{E_t}|\\ &=\mathcal{H}(\Omega \cap \partial E_t)\\ &=\mathcal{H}(\Omega \cap \{x| a\cdot x +b=t\})\\ &=\int_{\Omega \cap \{x| a\cdot x +b=t\}} d\mathcal{H}^{N-1}(x)\\ &=\int_{\{x| a\cdot x +b=t\}}\chi_{\Omega}(x)\, d\mathcal{H}^{N-1}(x) \end{align*}
Thus we get,
\begin{align*} &\int_{-\infty}^{\infty} \int_{\Omega} |D\chi_{E_t}|\, dx dt\\ &=|a|\mathcal{L}(\Omega)\\ &=\int_{\{x| a\cdot x +b=t\}}\chi_{\Omega}(x)\, d\mathcal{H}^{N-1}(x)\\ &=\int_{\Omega} |Du| \end{align*}
Hence we have,
\begin{align*} \int_{-\infty}^{\infty} \int_{\Omega} |D\chi_{E_t}|\, dx dt=|Du|(\Omega) \dots \mbox{ if } u=a\cdot x+b. \end{align*}

Step ii. Now we prove that \int_{-\infty}^{\infty} \int_{\Omega} |D\chi_{E_t}|\, dx dt\leq|Du|(\Omega) for all u\in BV(\Omega). We know that the space of piecewise linear and continuous functions \mathcal{A}(\Omega) is dense in W^{1, 1}(\Omega) when equipped with the strong topology. We also know that the space C^{\infty}\cap W^{1, 1}(\Omega) is dense in BV when equipped with the intermediate convergence. Thus, there exists a sequence \{u_n\}_{n\in \mathbb{N}} \in \mathcal{A}(\Omega) such that u_n\rightharpoonup u for the intermediate convergence. For each of the functions u_n we set E_{n, t}:=\{x\in \Omega: u_n(x) > t\}. Due to the intermediate convergence, we have
\begin{align*} &\int_{\Omega}|Du|=\lim_{n\rightarrow \infty}\int_{\Omega}|Du_n| \dots \mbox{the intermediate convergence}\\ &=\lim_{n\rightarrow \infty} \int_{-\infty}^{\infty} \int_{\Omega} |D\chi_{E_{n,t}}|\, dx dt \dots \mbox{from step i}\\ &\geq \int_{-\infty}^{\infty} \lim\inf_{n\rightarrow \infty} \int_{\Omega} |D\chi_{E_{n,t}}|\, dx dt \dots \mbox{Fatou's lemma}\\ \end{align*}
From the intermediate convergence we also have u_n\rightarrow u in L^1(\Omega). i.e.
\begin{align*} \int_{\Omega} |u_n-u|=\int_{\Omega} \int_{-\infty}^{\infty} |\chi_{E_{n,t}}-\chi_{E_t}|\ dt dx = \int_{-\infty}^{\infty} \Big(\int_{\Omega} |\chi_{E_{n,t}}-\chi_{E_t}|\ dx \Big) dt=0. \end{align*}
Thus, for a subsequence E_{n_m, t}, and for almost all t \in \mathbb{R}, \chi_{E_{n_m, t}}\rightarrow \chi_{E_{n, t}} strongly in L^1(\Omega). The lower semicontinuity of the total variation with respect to the strong convergence in L^1(\Omega) we get \lim\inf_{n\rightarrow \infty} \int_{\Omega} |D\chi_{E_{n_m,t}}|\, dx \geq \int_{\Omega} |D\chi_{E_{t}}|\, dx. Thus, we get,
\int_{\Omega}|Du| \geq \int_{-\infty}^{\infty} \int_{\Omega} |D\chi_{E_{t}}|\, dx dt.
This completes the proof!

(By the way, step ii also proves that D\chi_{E_t} \in \mathbf{M}(\Omega, \mathbb{R}^N) for a.e. t\in \mathbb{R}, something that we used in Part I of the proof.)



Thursday, August 9, 2012

Hausdorff measure and dimension

Let us talk about Hausdorff measure \mathcal{H}^s named after Felix Hausdorff, which comes up in image processing often. These measures allow us to measure very small subsets of \mathbb{R}^n. The idea is that A is an s- dimensional subset of \mathbb{R}^n if 0<\mathcal{H}^s(A)<\infty. We will follow the notation and treatment of Evans and Gariepy.



Felix Hausdorff
Definitions:
(i) Let A\subset \mathbb{R}^n, 0\leq s < \infty, 0<\delta\leq \infty. Define \mathcal{H}^s_{\delta}(A)=\inf \Big\{ \sum_{j=1}^{\infty} \alpha(s) \Big( \frac{\mbox{diam}(C_j)}{2} \Big)^s \, \Big\vert \,A\subset \cup_{j=1}^{\infty}C_j, \mbox{diam}(C_j)\leq \delta \Big\}, where \{C_j\}\subset \mathbb{R}^n is the covering of the set A and \alpha(s)=\frac{\pi^{\frac{s}{2}}}{\Gamma(\frac{s}{2}+1)}. Here \Gamma(s)=\int_0^{\infty}e^{-x}x^{s-1}\,dx,\,\,(0< s<\infty), is the usual gamma function. (ii) The s-dimensional Hausdorff measure of A is denoted by \mathcal{H}^s(A) and it is defined as the limit:
\mathcal{H}^s(A)=\lim_{\delta\rightarrow 0}\mathcal{H}^s_{\delta}(A)=\sup_{\delta >0} \mathcal{H}^s_{\delta}(A).

The book: 'Measure theory and fine properties of functions' by Evans and Gariepy includes the normalizing constant \alpha(s) in the definition, whereas some other authors do not include this constant. The constant \alpha(s) is included because if s is an integer, then \mathcal{H}^s(A) is equal to the s-dimensional surface area for nice sets (graph of Lipschitz function).


Some properties of Hausdorff measure:
1.\mathcal{H}^s is a Borel regular measure. Refer to E.G. for the proof.

2. Let us consider a Hausdorff measure \mathcal{H}^0 of a singleton \{a\}\in \mathbb{R}^n. First note that \alpha(0)=1. So, \mathcal{H}^0(\{a\})=\mathcal{H}^0_{\delta}(\{a\})=1. Thus, \mathcal{H}^0 is a counting measure.

3. \mathcal{H}^1=\mathcal{L}^1 on \mathbb{R}^1, i.e. \mathcal{H}^1 measure of a line segment is its length.

4. Since \mathbb{R}^n is not \sigma-finite, \mathcal{H}^s is not a Radon measure for 0\leq s < n.

5. If s > n then \mathcal{H}^s\equiv 0 on \mathbb{R}^n.
To see this is easy. Let us consider a unit cube Q in \mathbb{R}^n, fix an integer m \geq 1. The unit cube can be decomposed into m^n cubes with sides 1/m and diameter {n^{1/2}}/{m}. Therefore,
\mathcal{H}^s_{{\sqrt{n}}/{m}}(Q)\leq \sum_{i=1}^{m^n} \alpha(s) (n^{1/2}/m)^s = \alpha(s) n^{s/2} m^{n-s}.If s >n, then m^{n-s}\rightarrow 0 as m\rightarrow \infty i.e. as the size of the covering vanishes. Thus, \mathcal{H}^s(Q)=0, so \mathcal{H}^s(\mathbb{R}^n)=0 for s >n.

6. Scaling: \mathcal{H}^s(\lambda A)=\lambda^s\mathcal{H}^s(A) for all \lambda > 0, A \subset \mathbb{R}^n. (Easy to prove.)

7. Invariance under affine transformation: \mathcal{H}^s(L(A))=\mathcal{H}^s(A) for each affine isometry L:\mathbb{R}^n\rightarrow \mathbb{R}^n, \, A \subset \mathbb{R}^n.

8. \mathcal{H}^n=\mathcal{L}^n on \mathbb{R}^n.


Hausdorff-Besicovitch dimension:
The hausdorff dimension of a set A\subset \mathbb{R}^n is defined to be

\mathcal{H}_{\mbox{dim}}(A)=\inf\{ 0\leq s < \infty | \mathcal{H}^s(A)=0 \}.

The following assertions follow from the definition:
Countable sets have Hausdorff dimension 0. The Euclidean space has Hausdorff dimension n.
The circle has Hausdorff dimension 1.
The Cantor set (a zero-dimensional topological space) is a union of two copies of itself, each copy shrunk by a factor 1/3; this fact can be used to prove that its Hausdorff dimension is {\ln 2}/{\ln 3}.