Recovery of Blocky Images in Electrical Impedance Tomography

The techniques of electrical impedance tomography (EIT) have been widely studied over the past several years, for applications in both medical imaging and nondestructive evaluation. The goal is to find the electrical conductivity of a spatially inhomogeneous medium inside a given domain, using electrostatic measurements collected at the boundary.

[1]  E. Giusti Minimal surfaces and functions of bounded variation , 1977 .

[2]  T. Coleman,et al.  A global and quadratically convergent method for linear l ∞ problems , 1992 .

[3]  David C. Dobson,et al.  Estimates on resolution and stabilization for the linearized inverse conductivity problem , 1992 .

[4]  M. K. Pidcock,et al.  Some Mathematical Aspects of Electrical Impedance Tomography , 1988 .

[5]  Jianguo Liu,et al.  An interior Newton method for quadratic programming , 1993, Math. Program..

[6]  Fadil Santosa,et al.  Stability and resolution analysis of a linearized problem in electrical impedance tomography , 1991 .

[7]  D. Donoho Superresolution via sparsity constraints , 1992 .

[8]  P. Lions,et al.  Image selective smoothing and edge detection by nonlinear diffusion. II , 1992 .

[9]  David C. Dobson,et al.  Exploiting ill-posedness in the design of diffractive optical structures , 1993, Smart Structures.

[10]  Yuying Li,et al.  An Affine Scaling Algorithm for Minimizing Total Variation in Image Enhancement , 1994 .

[11]  Fadil Santosa,et al.  Resolution and Stability Analysis of an Inverse Problem in Electrical Impedance Tomography: Dependence on the Input Current Patterns , 1994, SIAM J. Appl. Math..

[12]  Curtis R. Vogel,et al.  Iterative Methods for Total Variation Denoising , 1996, SIAM J. Sci. Comput..

[13]  Michel Barlaud,et al.  Deterministic edge-preserving regularization in computed imaging , 1997, IEEE Trans. Image Process..

[14]  Curtis R. Vogel,et al.  Fast numerical methods for total variation minimization in image reconstruction , 1995, Optics & Photonics.

[15]  K. Kunisch,et al.  An active set strategy based on the augmented Lagrangian formulation for image restoration , 1999 .

[16]  Raymond H. Chan,et al.  Continuation method for total variation denoising problems , 1995, Optics & Photonics.

[17]  Gene H. Golub,et al.  Matrix computations , 1983 .

[18]  Donald Geman,et al.  Nonlinear image recovery with half-quadratic regularization , 1995, IEEE Trans. Image Process..

[19]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[20]  D. Dobson,et al.  An image-enhancement technique for electrical impedance tomography , 1994 .

[21]  Fadil Santosa,et al.  Recovery of Blocky Images from Noisy and Blurred Data , 1996, SIAM J. Appl. Math..

[22]  Fadil Santosa,et al.  Reconstruction of blocky impedence profiles from normal-incidence reflection seismograms which are band-limited and miscalibrated , 1988 .

[23]  P. Lions,et al.  Image recovery via total variation minimization and related problems , 1997 .

[24]  L. Rudin,et al.  Feature-oriented image enhancement using shock filters , 1990 .

[25]  F. Santosa,et al.  Linear inversion of ban limit reflection seismograms , 1986 .