A joint acquisition-reconstruction paradigm for correcting inhomogeneity artifacts in MR echo planar imaging.

One of the main sources of signal degradation in rapid MR acquisitions, such as Echo Planar Imaging (EPI), is magnetic field variations caused by field inhomogeneities and susceptibility gradients. If unaccounted for during the reconstruction process, this spatially-varying field can cause severe image artifacts. In this paper, we show that correcting for the resulting degradations can be formulated as a blind image deconvolution problem.

Resource-constrained rate control for Motion JPEG2000.

With the increasing importance of heterogeneous networks and time-varying communication channels, fine scalability has become a highly desirable feature in both image and video coders. A single highly scalable bitstream can provide precise rate control for constant bitrate (CBR) traffic and accurate quality control for variable bitrate (VBR) traffic. We first propose two leaky-bucket rate allocation methods that provide constant quality video under buffer constraints.

Collaborative multihop transmission of distributed sensor imagery.

We consider a network of imaging sensors. We address the problem of energy-efficient communication of the measurements of the sensors. A novel algorithm is presented for the purpose of exploiting intersensor and intrasensor correlation, which is inherent in a network of imaging sensors.

A method for coordinating the distributed transmission of imagery.

Distributed imaging using sensor arrays is gaining popularity among various research and development communities. A common bottleneck within such an imaging sensor network is the large resulting data load. In applications for which transmission power and/or bandwidth are constrained, this can drastically decrease the sensor network lifetime.

Efficient storage and transmission of ladar imagery.

We develop novel methods for compressing volumetric imagery that has been generated by single-platform (mobile) range sensors. We exploit the correlation structure inherent in multiple views in order to improve compression efficiency. We show that, for lossless compression, three-dimensional volumes compress more efficiently than two-dimensional (2D) images by a factor of 60%.