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Robust Color Image Superresolution: An Adaptive M-Estimation Framework

Abstract

This paper introduces a new color image superresolution algorithm in an adaptive, robust M-estimation framework. Using a robust error norm in the objective function, and adapting the estimation process to each of the low-resolution frames, the proposed method effectively suppresses the outliers due to violations of the assumed observation model, and results in color superresolution estimates with crisp details and no color artifacts, without the use of regularization. Experiments on both synthetic and real sequences demonstrate the superior performance over using the and error norms in the objective function.

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Correspondence to NohaA El-Yamany.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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El-Yamany, N., Papamichalis, P. Robust Color Image Superresolution: An Adaptive M-Estimation Framework. J Image Video Proc 2008, 763254 (2008). https://doi.org/10.1155/2008/763254

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Keywords

  • Objective Function
  • Image Processing
  • Pattern Recognition
  • Computer Vision
  • Error Norm