Principal Component Analysis for Acceleration of Color Guided Image Filtering

In this paper, we propose an acceleration of guided image filtering, which is one of the fastest edge-preserving filters. The proposed method converts RGB signals into a color space introduced by the principal component analysis. Then, the filtering signals are sub-sampled or approximated by simple box filtering in the biased color space. The experimental results show that the proposed method is superior to the conventional acceleration method in accuracy and computational time.

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