Two-Pass Bilateral Smooth Filtering for Remote Sensing Imagery

Bilateral filtering has been adopted for edge-preserving image smoothing and achieved the state-of-the-art performance. Most of the existing bilateral filters (BFs), however, focus on accelerating brute-force implementation but not on smoothing quality. In this letter, we propose a two-pass (TP) BF,...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Main Authors: Chen, Bo-Hao, Cheng, Hsiang-Yin, Tseng, Yi-Syuan, Yin, Jia-Li
Format: Article
Language:English
Subjects:
Adaptive control
Bilateral filtering
edge-preserving image smoothing
Filtering
Filtration
Fine structure
Histograms
Image edge detection
Imagery
incoherent noise
Kernel
Kernels
Pixels
Remote sensing
Smoothing
Smoothing methods
Ultrastructure
Visualization
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Summary:Bilateral filtering has been adopted for edge-preserving image smoothing and achieved the state-of-the-art performance. Most of the existing bilateral filters (BFs), however, focus on accelerating brute-force implementation but not on smoothing quality. In this letter, we propose a two-pass (TP) BF, TP-based BF, and an adaptive control scheme of range kernels for noise-invariant edge-preserving image smoothing. Specifically, the TP-based BF is composed of two bilateral filtering operations, which are, respectively, in charge of coarse context extraction and fine structure refinement. The control scheme of range kernels guides the TP bilateral mechanism to eliminate first high-frequency noisy pixels and then explore contribution between pixels from clean contexts. Experimental results on four aerial-imagery benchmark data sets show that our TP-based BF outperforms the existing BFs in terms of both feature- and gradient-aware measures.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2020.3048488