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Standard blurring removes noise from images, but tends to smooth away edges in the process. This anisotropic filter preserves edges better.
blur_anisotropic( im, amplitude, sharpness = 0.7, anisotropy = 0.6, alpha = 0.6, sigma = 1.1, dl = 0.8, da = 30, gauss_prec = 2, interpolation_type = 0L, fast_approx = TRUE )
an image
Amplitude of the smoothing.
Sharpness.
Anisotropy.
Standard deviation of the gradient blur.
Standard deviation of the structure tensor blur.
Spatial discretization.
Angular discretization.
Precision of the diffusion process.
Interpolation scheme. Can be 0=nearest-neighbor | 1=linear | 2=Runge-Kutta
If true, use fast approximation (default TRUE)
cimg.limit.openmp() im <- load.image(system.file('extdata/Leonardo_Birds.jpg',package='imager')) im.noisy <- (im + 80*rnorm(prod(dim(im)))) blur_anisotropic(im.noisy,ampl=1e4,sharp=1) %>% plot
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