LAUSR

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.