pad_image_to_fft

deeptrack.image.pad_image_to_fft(image: Image | ndarray, axes: Iterable[int] = (0, 1)) → Image | ndarray

Pads an image to optimize Fast Fourier Transform (FFT) performance.

This function pads an image by adding zeros to the end of specified axes so that their lengths match the nearest larger size in _FASTEST_SIZES. These sizes are selected to optimize FFT computations.

Parameters

imageImage or np.ndarray

The input image to pad. It should be an instance of the Image class or any array-like structure compatible with FFT operations.

axesIterable[int], optional

The axes along which to apply padding. Defaults to (0, 1).

Returns

Image or np.ndarray

The padded image with dimensions optimized for FFT performance.

Raises

ValueError

If no suitable size is found in _FASTEST_SIZES for any axis length.

Example

>>> import numpy as np
>>> from deeptrack.image import Image, pad_image_to_fft

Pad an Image object:

>>> img = Image(np.zeros((7, 13)))
>>> padded_img = pad_image_to_fft(img)
>>> print(padded_img.shape)
(8, 16)

Pad a NumPy array:

>>> img = np.zeros((5, 11)))
>>> padded_img = pad_image_to_fft(img)
>>> print(padded_img.shape)
(6, 12)