def filter_lowpass(im, cutoffFrequency, order=1, filterShape=ipcv.IPCV_IDEAL):
"""
Function to generate a lowpass filter for the shape of a given image
Args:
im (array): source image, needed for the shape of the filter
cutoffFrequency (int): the frequency at which the filter stops
order (optional[int]): the order of the power for non-ideal filters
filterShape (optional[int]): Frequency filter shapes,
defined in constants.py, defaults to ideal filter
Return:
the filter for the image, as numpy.float64 data types
"""
distanceArray = ipcv.filter_distance(im).astype(np.float64)
filterFunction = {
ipcv.IPCV_IDEAL: ideal_lowpass,
ipcv.IPCV_BUTTERWORTH: butterworth_lowpass,
ipcv.IPCV_GAUSSIAN: gaussian_lowpass
}
return filterFunction[filterShape](distanceArray, cutoffFrequency, order)
def filter_highpass(im, cutoffFrequency, order=1, filterShape=ipcv.IPCV_IDEAL):
"""
Function to generate a highpass filter for the shape of a given image
Args:
im (array): source image, needed for the shape of the filter
cutoffFrequency (int): the frequency at which the filter stops
order (optional[int]): the order of the power for non-ideal filters
filterShape (optional[int]): Frequency filter shapes,
defined in constants.py, defaults to ideal filter
Return:
the filter for the image, as numpy.float64 data types
"""
distanceArray = ipcv.filter_distance(im).astype(np.float64)
filterFunction = {
ipcv.IPCV_IDEAL : ipcv.ideal_lowpass,
ipcv.IPCV_BUTTERWORTH : ipcv.butterworth_lowpass,
ipcv.IPCV_GAUSSIAN : ipcv.gaussian_lowpass
}
return 1-filterFunction[filterShape](distanceArray, cutoffFrequency, order)
def filter_bandpass(im, radialCenter, bandwidth, order=1, filterShape=ipcv.IPCV_IDEAL):
"""
Function to generate a bandpass filter for the shape of a given image
Args:
im (array): source image, needed for the shape of the filter
radialCenter (int): the frequency at which the filter stops
brandwidth (int): the width of the band
order (optional[int]): the order of the power for non-ideal filters
filterShape (optional[int]): Frequency filter shapes,
defined in constants.py, defaults to ideal filter
Return:
the filter for the image, as numpy.float64 data types
"""
distanceArray = ipcv.filter_distance(im).astype(np.float64)
filterFunction = {
ipcv.IPCV_IDEAL : ipcv.ideal_bandreject,
ipcv.IPCV_BUTTERWORTH : ipcv.butterworth_bandreject,
ipcv.IPCV_GAUSSIAN : ipcv.gaussian_bandreject
}
return 1-filterFunction[filterShape](distanceArray, radialCenter, bandwidth, order)
