Two-dimensional signal deconvolution: design issues related to a novel multisensor-based approach

Nicholaos D. Sidiropoulos; John S. Baras; Carlos A. Berenstein

doi:10.1117/12.48393

1 October 1991 Two-dimensional signal deconvolution: design issues related to a novel multisensor-based approach

Nicholaos D. Sidiropoulos, John S. Baras, Carlos A. Berenstein

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48393
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

Recent results of analysis in several complex variables are employed to come up with a set of compactly supported approximate deconvolution kernels for the reconstruction of a two- dimensional signal based on multiple linearly degraded versions of the signal with a family of kernels that satisfies suitable technical conditions. The question of convergence of the proposed deconvolution kernels are discussed, simulation results that demonstrate the gain in bandwidth are presented, and two data parallel grid layouts for the off-line computation of the deconvolution kernels are proposed.

Citation Download Citation

Nicholaos D. Sidiropoulos, John S. Baras, and Carlos A. Berenstein "Two-dimensional signal deconvolution: design issues related to a novel multisensor-based approach", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48393

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