Mohamed Khames Ben Hadj Miled

Recent work in shape-based methods for diffusive inverse problems

We consider geometric inversion methods designed to directly determine information concerning the size, shape, location, and perhaps number of anomalies in a region of interest [E. L. Miller, M. E. Kilmer, and C. M. Rappaport, IEEE Trans. Geosci. Remote Sens. 38, 1682 (2000); O. Dorn, E. L. Miller, and C. Rappaport, Inverse Probl. 16, 1119 (2000)] for diffusive inverse problems arising in medical imaging and environmental remediation. First, a parametric approach to the problem is derived and validated using a diffuse optical tomography sensing example. A second technique to identify boundaries of an unknown number of objects is based on the idea of curve evolution. This approach mathematically “shrink wraps” a deformable surface in 3D or curve in 2D to the boundary of one or more objects. We demonstrate the utility of this method using an electrical resistance tomography sensing example in three dimensions.

JPEG 2000 for wireless applications

JPEG2000 is the new ISO/IEC image compression standard. It is a full coding system targeted for various imaging applications. Besides offering the state-of-the-art in still image compression, it provides new features such as scalability in quality and in resolution, random access and region of interest (ROI) coding. Motion JPEG2000 is an inherited video compression standard based on intra-farme coding using JPEG2000. JPIP (the JPEG2000 Interactive Protocol), is a developing protocol for the access and transmission of JPEG2000 coded data and related metadata in a networked environment. In this paper, we present various applications of JPEG2000, Motion JPEG2000 and JPIP, geared specially towards the wireless mobile environment. We present an Image Surfing system for surfing JPEG2000 images on mobile terminals over a wireless network. We also present a scheme for tracking and coding Regions-Of-Interest (ROI) over a Motion JPEG2000 sequence. Finally, we present a Partial Coding scheme for use in Motion JPEG2000 sequences that gives coding gains for certain types of video sequences.

On the extension of level-set curve evolution methods for low-sensitivity imaging problems

We address inverse medium problems characterized by low-sensitivity observation data. A new level-set based method to recover the structure of piecewise homogeneous media is proposed. We make two contributions to this area of research. First, we capitalize on the flexibility in specifying the level-set velocity function in a way which counteracts the low sensitivity characteristic of the problem. The new approach speeds convergence while keeping the level set function smooth. Second, extending the current state of the art in the use of level sets for known binary media, we describe a simple and efficient implementation for N-ary media problems. We restrict our application examples to the electrical resistance tomography (ERT) problem, however, the proposed approaches are applicable to a variety of inverse problems involving shape reconstruction. We demonstrate the utility of our approach through a series of simulations using synthetic ERT data. Despite the ill-posed nature of the ERT problem, the simulation results show quite accurate estimations of the locations, sizes and shapes of multiple spatial inhomogeneities.