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Cross-Based Adaptive Guided Filtering
Ming Yan, Yueli Hu, Kai Li, Jianeng Zhao
30 - 39
10.3233/FAIA200763
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 332: Machine Learning and Artificial Intelligence
Abstract

Edge-preserving and structure-preserving smoothing filtering has attracted much interest in the last decades. A conventional linear filter effectively smoothens noise in homogeneous regions but blurs the edges of an image. This study aimed to present an adaptive guided filter using a cross-based framework. The proposed method outperformed many other algorithms in terms of sharpness enhancement and noise reduction. Moreover, the cross-based adaptive guided filter had a fast and nonapproximate linear-time algorithm as the guided filter.

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