Principal component analysis for accelerating color bilateral filtering

Kazuya Ishikawa; Sou Oishi; Norishige Fukushima

doi:10.1117/12.2666984

25 March 2023 Principal component analysis for accelerating color bilateral filtering

Kazuya Ishikawa, Sou Oishi, Norishige Fukushima

Proceedings Volume 12592, International Workshop on Advanced Imaging Technology (IWAIT) 2023; 125921F (2023) https://doi.org/10.1117/12.2666984
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2023, 2023, Jeju, Korea, Republic of

Abstract

In this paper, we propose to speed up bilateral filtering by principal component analysis (PCA)-based dimensionality compression method with constant-time bilateral filtering. Constant-time bilateral filtering speeds up the filtering by representing it as a summation of the multiple Gaussian filters. However, a simple implementation is of the order of O(K³) for color and suffers from the curse of dimensionality. A clustering-based approximation speedup solves this problem with an order of O(K) or O(K²). PCA can provide a more informative signal relative to the transformation matrix. We have accelerated the process by converting the color information of the input image from 3-channel to 1-channel by PCA, considering the constant-time bilateral filter as joint bilateral filtering, and using the transformed image as a guide image. This dimensional reduction allowed us to filter images with sufficient accuracy at a higher speed.

Citation Download Citation

Kazuya Ishikawa, Sou Oishi, and Norishige Fukushima "Principal component analysis for accelerating color bilateral filtering", Proc. SPIE 12592, International Workshop on Advanced Imaging Technology (IWAIT) 2023, 125921F (25 March 2023); https://doi.org/10.1117/12.2666984

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