Optical sensed image fusion with dynamic neural networks

Yuri V. Shkvarko; Oscar G. Ibarra-Manzano; Rene Jaime-Rivas; Jose A. Andrade-Lucio; Edgar Alvarado-Mendez; R. Rojas-Laguna; Miguel Torres-Cisneros; J. A. Alvarez-Jaime

doi:10.1117/12.437178

14 August 2001 Optical sensed image fusion with dynamic neural networks

Yuri V. Shkvarko, Oscar G. Ibarra-Manzano, Rene Jaime-Rivas, Jose A. Andrade-Lucio, Edgar Alvarado-Mendez, R. Rojas-Laguna, Miguel Torres-Cisneros, J. A. Alvarez-Jaime

Author Affiliations +

Proceedings Volume 4419, 4th Iberoamerican Meeting on Optics and 7th Latin American Meeting on Optics, Lasers, and Their Applications; (2001) https://doi.org/10.1117/12.437178
Event: IV Iberoamerican Meeting of Optics and the VII Latin American Meeting of Optics, Lasers and Their Applications, 2001, Tandil, Argentina

Abstract

The neural network-based technique for improving the quality of the image fusion is proposed as required for the remote sensing (RS) imagery. We prose to exit information about the point spread functions of the corresponding RS imaging systems combining it with prior realistic knowledge about the properties of the scene contained in the maximum entropy (ME) a priori image model. Applying the aggregate regularization method to solve the fusion tasks aimed to achieve the best resolution and noise suppression performances of the overall resulting image solves the problem. The proposed fusion method assumes the availability to control the design parameters, which influence the overall restoration performances. Computationally, the fusion method is implemented using the maximum entropy Hopfield-type neural network with adjustable parameters. Simulations illustrate the improved performances of the developed MENN-based image fusion method.

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Yuri V. Shkvarko, Oscar G. Ibarra-Manzano, Rene Jaime-Rivas, Jose A. Andrade-Lucio, Edgar Alvarado-Mendez, R. Rojas-Laguna, Miguel Torres-Cisneros, and J. A. Alvarez-Jaime "Optical sensed image fusion with dynamic neural networks", Proc. SPIE 4419, 4th Iberoamerican Meeting on Optics and 7th Latin American Meeting on Optics, Lasers, and Their Applications, (14 August 2001); https://doi.org/10.1117/12.437178

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KEYWORDS

Image fusion

Remote sensing

Neural networks

Systems modeling

Imaging systems

Point spread functions

Fusion energy

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