sarGen: Stochastic Autoregressive Image Generator

In spc4sts: Statistical Process Control for Stochastic Textured Surfaces

Stochastic Autoregressive Image Generator

Description

Generates a 2D stochastic AR(1) image.

Usage

sarGen(phi1 = .6, phi2 = .35, sigma = .01, m = 250, n = 250, border = 200)

Arguments

phi1	the parameter phi1 of the process.
phi2	the parameter phi2 of the process.
sigma	the parameter sigma of the process.
m	the number of rows of the generated image.
n	the number of columns of the generated image.
border	the number of top rows/left columns to be cut off from the generated image. This helps reduce the effect of the starting condition.

Details

The pixel y(i,j) of the 2D AR(1) process satisfies: y(i,j) = phi1*y(i-1,j) + phi2*y(i,j-1) + e(i,j), where e(i,j) follows a zero-mean Gaussian distribution with standard deviation of sigma. The process is then rescaled to [0, 255] to produce a greyscale image.

Value

The generated image in the matrix format.

Author(s)

Anh Bui

References

Bui, A.T. and Apley., D.W. (2018a) "A Monitoring and Diagnostic Approach for Stochastic Textured Surfaces", Technometrics, 60, 1-13.

See Also

imposeDefect

Examples

## generate an image without defects
img <- sarGen(m = 100, n = 100, border = 50)
image(img,col=gray(c(0:32)/32))

spc4sts documentation built on May 24, 2022, 5:07 p.m.