Real-Time Reconstruction of Remote Sensing Imagery: Aggregation of Robust Regularization with Neural Computing
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Fecha
2005
Autores
Shkvarko, Yuriy
Villalón-Turrubiates, Iván E.
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Editor
Association for Mathematics and Computers in Simulation
Resumen
Descripción
The robustified numerical technique for real-time sensor array reconstructive image processing is developed as required for remote sensing imaging with large scale array/synthesized array radars. The addressed technique is designed via performing the regularized robustification of the fused Bayesian-regularization imaging method aggregated with the efficient real-time numerical implementation scheme that employs the neural network computing.
Palabras clave
Image Reconstruction, Regularization, Neural Networks
Citación
Y. Shkvarko & I.E. Villalón-Turrubiate (2005), “Real-Time Reconstruction of Remote Sensing Imagery: Aggregation of Robust Regularization with Neural Computing”. Proceedings of the 17th International Association for Mathematics and Computers in Simulation (IMACS) World Congress, París, Francia.