nabu.misc.fourier_filters module

Fourier filters.

nabu.misc.fourier_filters.get_lowpass_filter(img_shape, cutoff_par=None, use_rfft=False, data_type=<class 'numpy.float64'>)[source]

Computes a low pass filter using the erfc function.

Parameters:

  • img_shape (tuple) – Shape of the image

  • cutoff_par (float or sequence of two floats) – Position of the cut off in pixels, if a sequence is given the second float expresses the width of the transition region which is given as a fraction of the cutoff frequency. When only one float is given for this argument a gaussian is applied whose sigma is the parameter. When a sequence of two numbers is given then the filter is 1 ( no filtering) till the cutoff frequency while a smooth erfc transition to zero is done

  • use_rfft (boolean, optional) – Creates a filter to be used with the result of a rfft type of Fourier transform. Defaults to False.

  • data_type (numpy.dtype, optional) – Specifies the data type of the computed filter. It defaults to numpy.float64

Raises:

ValueError – In case of malformed cutoff_par

Returns:

The computed filter

Return type:

numpy.array_like

nabu.misc.fourier_filters.get_highpass_filter(img_shape, cutoff_par=None, use_rfft=False, data_type=<class 'numpy.float64'>)[source]

Computes a high pass filter using the erfc function.

Parameters:

  • img_shape (tuple) – Shape of the image

  • cutoff_par (float or sequence of two floats) – Position of the cut off in pixels, if a sequence is given the second float expresses the width of the transition region which is given as a fraction of the cutoff frequency. When only one float is given for this argument a gaussian is applied whose sigma is the parameter, and the result is subtracted from 1 to obtain the high pass filter When a sequence of two numbers is given then the filter is 1 ( no filtering) above the cutoff frequency and then a smooth transition to zero is done for smaller frequency

  • use_rfft (boolean, optional) – Creates a filter to be used with the result of a rfft type of Fourier transform. Defaults to False.

  • data_type (numpy.dtype, optional) – Specifies the data type of the computed filter. It defaults to numpy.float64

Raises:

ValueError – In case of malformed cutoff_par

Returns:

The computed filter

Return type:

numpy.array_like

nabu.misc.fourier_filters.get_bandpass_filter(img_shape, cutoff_lowpass=None, cutoff_highpass=None, use_rfft=False, data_type=<class 'numpy.float64'>)[source]

Computes a band pass filter using the erfc function.

The cutoff structures should be formed as follows:

  • tuple of two floats: the first indicates the cutoff frequency, the second determines the width of the transition region, as fraction of the cutoff frequency.

  • one float -> it represents the sigma of a gaussian which acts as a filter or anti-filter (1 - filter).

Parameters:

  • img_shape (tuple) – Shape of the image

  • cutoff_lowpass (float or sequence of two floats) – Cutoff parameters for the low-pass filter

  • cutoff_highpass (float or sequence of two floats) – Cutoff parameters for the high-pass filter

  • use_rfft (boolean, optional) – Creates a filter to be used with the result of a rfft type of Fourier transform. Defaults to False.

  • data_type (numpy.dtype, optional) – Specifies the data type of the computed filter. It defaults to numpy.float64

Raises:

ValueError – In case of malformed cutoff_par

Returns:

The computed filter

Return type:

numpy.array_like