On the origin of the bilateral filter and ways to improve it

By Michael Elad. IEEE Transactions on Image Processing, 2002

815 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/023b498568e7b7b916a1bd5b3480a84a20e74289

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

From Local Kernel to Nonlocal Multiple-Model Image Denoising (2009, methodology): “Signal-dependent weights (Section 2.5): Yaroslavsky Þlter [118], SUSAN Þlter [100], Sigma-Þlter [67], Bilateral Þlter [105],[ 24 ], kernel regression [103];”
Medical image processing on the GPU - Past, present and future (2013, methodology): “filtering (Tomasi and Manduchi, 1998; Elad, 2002), adaptive filtering (Knutsson et al.”
A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach (2006, background): “Several articles [Elad, 2002; Choudhury and Tumblin, 2003; Buades et al., 2005] extended the bilateral filter to a piecewise-linear assumption.”
Edge-preserving decompositions for multi-scale tone and detail manipulation (2008, methodology): “For example, [Elad 2002; Choudhury and Tum-blin 2003; Buades et al. 2006] extended the BLF to better handle piecewise linear functions.”
Urban-Area and Building Detection Using SIFT Keypoints and Graph Theory (2009, background): “Elad [5] shows that, bilateral filtering is closely related to edge preserving smoothing operations such as anisotropic diffusion.”
Guided Image Filtering (2010, background): “Empirically, the implicit weighted-average filters take at least a few seconds to process a one megapixel image either by preconditioning [41] or by multigrid [8].”
Fast Global Image Smoothing Based on Weighted Least Squares (2014, methodology): “Our method has a comparable runtime to the efficient EP filters, but the optimization formulation of our approach overcomes the limitations of previous filters in terms of smoothing quality, i.e. producing no halos (see Figure 1).”
Fast image and video denoising via nonlocal means of similar neighborhoods (2005, background): “…filter in [17], where the author proposes to average pixels close in space and gray values, as well as to the variations to this idea presented in [6], [9], [14], and [15] (see [2] for more details on these and other fundamental contributions to image denoising, together with comparisons and…”
Multiresolution Bilateral Filtering for Image Denoising (2008, unknown): “In [20], it is shown that the bilateral filter is identical to the first iteration of the Jacobi algorithm (diagonal normalized steepest descent) with a specific cost function .”
The Fast Bilateral Solver (2015, methodology): “Our pixel-space loss (Eq 1) resembles that of weighted least squares filtering [8, 9, 31], with one critical difference being our use of bilateral-space optimization which allows for efficient optimization even when using a large spatial support in the bilateral affinity, thereby improving the quali”
Single Image Super-Resolution With Non-Local Means and Steering Kernel Regression (2012, background): “Examples are edge-directed interpolation [3]–[5], normalized convolution [28], bilateral filter [29], [30], and steering kernel regression (SKR) [31].”