Total variation as a multiplicative constraint for solving inverse problems

نویسندگان

  • Aria Abubakar
  • Peter M. van den Berg
چکیده

The total variation minimization method for deblurring noise is shown to be effective in increasing the resolution in a contrast source inversion approach to index reconstruction from measured scattered field data. The main drawback is the presence of an artificial weighting parameter in the cost functional, which can only be determined through considerable experimentation Therefore, we introduce the total variation as a multiplicative constraint. Numerical examples demonstrate that the algorithm based on this multiplicative regularization seems to be robust and handling noisy data very well without the necessity of the weighting parameter.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Solving a New Multi-objective Inventory-Routing Problem by a Non-dominated Sorting Genetic Algorithm

This paper considers a multi-period, multi-product inventory-routing problem in a two-level supply chain consisting of a distributor and a set of customers. This problem is modeled with the aim of minimizing bi-objectives, namely the total system cost (including startup, distribution and maintenance costs) and risk-based transportation. Products are delivered to customers by some heterogeneous ...

متن کامل

An iterative method for the Hermitian-generalized Hamiltonian solutions to the inverse problem AX=B with a submatrix constraint

In this paper, an iterative method is proposed for solving the matrix inverse problem $AX=B$ for Hermitian-generalized Hamiltonian matrices with a submatrix constraint. By this iterative method, for any initial matrix $A_0$, a solution $A^*$ can be obtained in finite iteration steps in the absence of roundoff errors, and the solution with least norm can be obtained by choosing a special kind of...

متن کامل

An Iteratively Reweighted Algorithm for Sparse Reconstruction of Subsurface Flow Properties from Nonlinear Dynamic Data

A challenging problem in predicting fluid flow displacement patterns in subsurface environment is the identification of spatially variable flow-related rock properties such as permeability and porosity. Characterization of subsurface properties usually involves solving a highly underdetermined nonlinear inverse problem where a limited number of measurements are used to reconstruct a large numbe...

متن کامل

A New Method for Solving Constraint Satisfaction Problems

Many important problems in Artificial Intelligence can be defined as Constraint Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constraints on the values of those variables (these problems are also called Consistent Labeling Problems (CLP), in which “Labeling means assigning a value to a variable.) Solu...

متن کامل

Controlled Total Variation regularization for inverse problems

This paper provides a new algorithm for solving inverse problems, based on the minimization of the L2 norm and on the control of the Total Variation. It consists in relaxing the role of the Total Variation in the classical Total Variation minimization approach, which permits us to get better approximation to the inverse problems. The numerical results on the deconvolution problem show that our ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

دوره 10 9  شماره 

صفحات  -

تاریخ انتشار 2001