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Robust \(H_{\infty }\) deconvolution filtering of 2-D digital systems of orthogonal local descriptor

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Abstract

In this work, we propose a new set of \(H_{\infty }\) deconvolution filtering of 2-D color image using feature extraction of local descriptor and Fornasini-Machesini II (FM-II) model. The principal goal is to design 2-D deconvolution filter to reconstruct the noisy color image with the minimal information extracted from local Krawtchouk moment, Moreover, the filtering error system is asymptotically stable and satisfy the \(H_{\infty }\) performance index. the sufficient condition is given to ensure the \(H_{\infty }\) performance of the filtering error system through the Lyapunov theory, and the local Krawtckouk moment to give the feature extraction according to the order defined in advance instead of the global color image. Moreover, the 2-D deconvolution filter is designed to achieve the \(H_{\infty }\) performance index which the filter parameters are determined with certain optimization resolution. Finally, simulation example is provided to demonstrate the usefulness of the proposed design methods.

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Authors and Affiliations

  1. High Normal School, Department of Mathematics and Computer Sciences, Laboratory of Computer Sciences and Interdisciplinary Physics, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Mostafa El Mallahi

  2. Faculty of Sciences Dhar El Mahraz, Department of physics, Computer Science, Signals, Automation and Cognitivism Laboratory, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Bensalem Boukili, Amal Zouhri, Abdelaziz Hmamed & Hassan Qjidaa

Authors
  1. Mostafa El Mallahi
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  2. Bensalem Boukili
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  3. Amal Zouhri
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  4. Abdelaziz Hmamed
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  5. Hassan Qjidaa
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Correspondence to Mostafa El Mallahi.

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El Mallahi, M., Boukili, B., Zouhri, A. et al. Robust \(H_{\infty }\) deconvolution filtering of 2-D digital systems of orthogonal local descriptor. Multimed Tools Appl 80, 25965–25983 (2021). https://doi.org/10.1007/s11042-021-10845-9

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