DICpy.math4dic

DICpy.math4dic.derivatives(img1, img2=None)

First order derivatives in x, y, and time (for two images).

Input: * img1 (ndarray)

Image in time t.

• img2 (ndarray)

  Image in time t + dt.

Output/Returns: * gx (ndarray)

Derivative in x (columns) for img1.

• gy (ndarray)

  Derivative in y (rows) for img1.

• gt (ndarray)

  Derivative in time for img1 (optiional).

DICpy.math4dic.gradient(img, k)

Estimate the gradient of images using Sobel filters from OpenCV-Python.

Input: * img (ndarray)

Image.

• k (ndarray)

  Order of approximation.

Output/Returns: * gx (ndarray)

Derivative in x (columns).

• gy (ndarray)

  Derivative in y (rows).

DICpy.math4dic.interpolate_template(f=None, x=None, y=None, dx=0, dy=0, dim=None)

Method of interpolation.

Input: * f (ndarray)

Source image.

• x (ndarray)

  Integer pixel position in the x direction.

• y (ndarray)

  Integer pixel position in the y direction.

• dx (float)

  Sub-pixel increment in the x direction.

• dy (float)

  Sub-pixel increment in the y direction.

Output/Returns: * z (ndarray)

Interpolated image.

DICpy.math4dic.interpolate_template2(f=None, x=None, y=None, dx=0, dy=0)

Method of interpolation.

Input: * f (ndarray)

Source image.

• x (ndarray)

  Integer pixel position in the x direction.

• y (ndarray)

  Integer pixel position in the y direction.

• dx (float)

  Sub-pixel increment in the x direction.

• dy (float)

  Sub-pixel increment in the y direction.

Output/Returns: * z (ndarray)

Interpolated image.

DICpy.math4dic.norm_xcorr(f, g)

Normalized cross correlation.

Input: * f (ndarray)

Image.

• g (ndarray)

  Image.

Output/Returns: * c (float)

Correlation.