Unified Bayesian-Experiment Design Regularization Technique for High-Resolution Reconstruction of the Remote Sensing Imagery (original) (raw)
1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.
Related papers
Aggregation of Robust Regularization with Dynamic Filtration for Enhanced Radar Imaging
2006
The paper suggest a novel approach to the problem of high-resolution array radar/SAR imaging as an ill-conditioned inverse spatial spectrum pattern (SSP) estimation problem with model uncertainties. We explain the theory recently developed by the authors of this presentation that addresses a new fused Bayesian-regularization paradigm for radar/SAR image formation/reconstruction. We show how this theory leads to new adaptive and robustified computational methods that enable one to derive efficient and consistent estimates of the SSP via unifying the Bayesian minimum risk estimation strategy with the ME randomized a priori image model and other projection-type regularization constraints imposed on the solution. We detail such fused Bayesian-regularization (FBR) paradigm and analyze some efficient numerical schemes for computational implementation of the relevant FBR-based methods. Also, we present the results of extended simulation study of the family of the radar image (RI) formation...
2010
This study consider the problem of high-resolution imaging of the remote sensing (RS) environment formalized in terms of a nonlinear ill- posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the wavefield scattered from an extended remotely sensed scene (referred to as the scene image). However, the remote sensing techniques for reconstructive imaging in many RS application areas are relatively unacceptable for being implemented in a (near) real time implementation. In this work, we address a new aggregated descriptive-regularization (DR) method and the Hardware/Software (HW/SW) co-design for the SSP reconstruction from the uncertain speckle-corrupted measurement data in a computationally efficient parallel fashion that meets the (near) real time image processing requirements. The hardware design is performed via efficient systolic arrays (SAs). Finally, the efficiency both in resolution enhancement and in computational complexity reductio...
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.