Aggregation of Descriptive Regularization Methods with Hardware or Software Co-Design for Remote Serving Imaging (PDF01)

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Alejandro Castillo-Atoche, Ivan Villalón-Turrubiates and Javier Vázquez Castillo (Editors)
Universidad Autónoma de Yucatán, Mexico, and others

Series: Computer Science, Technology and Applications
BISAC: TEC008000

This new book considers 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. This book addresses 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. (Imprint: Nova)

Table of Contents

Table of Contents

ABSTRACT

1. INTRODUCTION

2. PROBLEM MODEL

3. HIGH-RESOLUTION DETERMINISTIC IMAGING TECHNIQUES

4. HW/SW CO-DESIGN ARCHITECTURE

5. SIMULATIONS AND PERFORMANCE ANALYSIS

6. CONCLUSION

REFERENCES

INDEX

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