Aggregation of Descriptive Regularization Methods with Hardware/Software Co-Design for Remote Sensing Imaging
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Fecha
2010
Autores
Castillo-Atoche, Alejandro
Villalón-Turrubiates, Iván E.
Vázquez-Castillo, Javier
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Editor
Nova Science Publishers
Resumen
Descripción
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 reduction metrics of the aggregated descriptive-regularized and the HW/SW co-design method is presented via numerical simulations and by the performance analysis of the implementation based on a Xilinx Field Programmable Gate Array (FPGA) XC4VSX35-10ff668.
Palabras clave
Descriptive Regularization, Remote Sensing, Image Reconstruction, Systolic Arrays, FPGA
Citación
A. Castillo-Atoche, I.E. Villalón-Turrubiates and J. Vázquez-Castillo. Aggregation of Descriptive Regularization Methods with Hardware/Software Co-Design for Remote Sensing Imaging. Ed. Nova Science Publishers, 2010.