Authors:
Sou Oishi
and
Norishige Fukushima
Affiliation:
Nagoya Institute of Technology, Japan
Keyword(s):
High-dimensional Gaussian Filtering, Approximated Acceleration, Clustering, Constant-time Filtering, Bilateral Filtering, Non-local means, Dual Bilateral Filtering, Cross Trilateral Filtering.
Abstract:
Edge-preserving filtering is an essential tool for image processing applications and has various types of filtering. For real-time applications, acceleration of its speed is also essential. To accelerate various types of edge-preserving filtering, we represent various edge-preserving filtering by high-dimensional Gaussian filtering. Then, we accelerate the high-dimensional Gaussian filtering by clustering-based constant algorithm, which has O(K) order, where K is the number of clusters. The clustering-based method was developed for color bilateral filtering; however, this paper used it for high-dimensional bilateral filtering. Also, cooperating with tiling, k-means++, and principal component analysis, we can further improve the filter’s performance. Experimental results show that our method can approximate various edge-preserving filtering by approximated clustering-based high-dimensional Gaussian filtering.