Skip to main content
Fig. 10 | Visual Computing for Industry, Biomedicine, and Art

Fig. 10

From: Intensity-curvature functional based digital high pass filter of the bivariate cubic B-spline model polynomial function

Fig. 10

Normal distribution values, calculated using the formula \( \mathrm{f}\left(\mathrm{x},\upmu, \sigma \right)=\left(\frac{1}{\sqrt{2\uppi \sigma }}\right){e}^{-\left[{\left(\mathrm{x}-\upmu \right)}^2/\left(2{\upsigma}^2\right)\right]} \), for the filtered images presented in Fig. 8 [see lines in (a)] and for the k-space images presented in Fig. 9 [see lines in (b)]. The plots show cumulative lines. Each line corresponds to an image, and displays the value of f(x, μ, σ) calculated using the value of ‘x’ (which is the histogram data of the image)

Back to article page