Antenna-based processing of the radar data for zone detection in remote sensing imagery

Authors

  • L. J. Morales-Mendoza CINVESTAV del IPN, Mexico
  • Yuriy V. Shkvarko CINVESTAV del IPN, Mexico
  • Jose Luis Leyva-Montiel CINVESTAV del IPN, Mexico
  • R. F. Vazquez-Bautista CINVESTAV del IPN, Mexico

DOI:

https://doi.org/10.1109/ICATT.2003.1238794

Keywords:

Gaussian noise, Hopfield neural nets, geophysical signal processing, image denoising, image enhancement, image reconstruction, iterative methods, maximum entropy methods, radar antennas, radar imaging, remote sensing by radar

Abstract

A new approach is addressed to perform antenna-based processing of radar imagery data aimed at reconstruction/enhancement of the images degraded by a spatially-shift-invariant radar spread function and contaminated with additive Gaussian noise. The fused maximum entropy-variational method is developed and computationally implemented using the modified Hopfield neural network. Enhanced zone detection and image denoising are achieved using the proposed approach.

References

Shkvarko, Yuriy; Shmaliy, Yuriy; Jaime-Rivas, R.; Torres-Cisneros, M. System Fusion in passive sensing using a modified Hopfield Network. Journal of the Franklin Institute, 2001.

Hamza, A. Ben; Krim, Hamid; Unal, Gozde B. Unifying Probabilistic and Variational Estimation. IEEE Trans. Signal Processing Magazine, Sept. 2002.

Black, Michael J.; Sapiro, Guillermo; Marimont, David H.; Heeger, David. Robust Anisotropic Diffusion. IEEE Trans. Signal Processing, Vol. 7, No. 3, Mar. 1998.

Perona, P.; Malik, J. Scale-Space and Edge Detection Using Anisotropic Diffusion. IEEE Trans. Pattern Analysis and Machine Intelligent, Vol. 12, No. 7, July 1990.

Zhou, Yi-Tong; Chellappa, Rama; Vaid, Aseem; Jenkins, B. Keith. Image Restoration Using a Neural Network. IEEE Trans. Acoustics, Speech and Signal Processing, Vol. 36, No. 7, July 1988.

Published

2003-09-25

Issue

Section

Broadband, multi-frequency antennas and remote sensing antennas