trackpy.preprocessing.bandpass¶

trackpy.preprocessing.bandpass(image, lshort, llong, threshold=None, truncate=4)¶

Remove noise and background variation.

Convolve with a Gaussian to remove short-wavelength noise and subtract out long-wavelength variations by subtracting a running average. This retains features of intermediate scale.

The lowpass implementation relies on scipy.ndimage.filters.gaussian_filter, and it is the fastest way known to the authors of performing a bandpass in Python.

Parameters:

imagendarray
lshortnumber or tuple: Size of the gaussian kernel with which the image is convolved. Provide a tuple for different sizes per dimension.
llonginteger or tuple: The size of rolling average (square or rectangular kernel) filter. Should be odd and larger than the particle diameter. When llong <= lshort, an error is raised. Provide a tuple for different sizes per dimension.
thresholdfloat or integer: Clip bandpass result below this value. Thresholding is done on the already background-subtracted image. By default, 1 for integer images and 1/255 for float images.
truncatenumber, optional: Determines the truncation size of the gaussian kernel. Default 4.

Returns:

resultarray: the bandpassed image