Robust color image superresolution: an adaptive M-estimation framework

Authors:
Noha A. El-Yamany;Panos E. Papamichalis
Affiliations:
Department of Electrical Engineering, School of Engineering, Southern Methodist University, Dallas, TX;Department of Electrical Engineering, School of Engineering, Southern Methodist University, Dallas, TX
Venue:
Journal on Image and Video Processing - Color in Image and Video Processing
Year:
2008

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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 L2 and L1 error norms in the objective function.