astro.deconvolution.deconvolve

DECONVOLVE.

This module defines functions to perform galaxy image deconvolution using the Condat-Vu algorithm.

psf_convolve(data, psf, psf_rot=False)

PSF Convolution.

Convolve the input data with the PSF provided.

Parameters

• data (numpy.ndarray) – Input data, 2D image

• psf (numpy.ndarray) – Input PSF, 2D image

• psf_rot (bool, optional) – Option to rotate the input PSF, default is False

Returns

Convolved image

Return type

numpy.ndarray

get_weights(data, psf, filters, wave_thresh_factor=array([3, 3, 4]))

Get Sparsity Weights.

Get the weights needed for the sparse regularisation term in the deconvolution problem.

Parameters

• data (numpy.ndarray) – Input data, 2D image

• psf (numpy.ndarray) – Input PSF, 2D image

• filters (numpy.ndarray) – Wavelet filters

• wave_thresh_factor (numpy.ndarray, optional) – Threshold factors for each wavelet scale, default is np.array([3, 3, 4])

Returns

Weights

Return type

numpy.ndarray

sparse_deconv_condatvu(data, psf, n_iter=300, n_reweights=1, verbose=False, progress=True)

Sparse Deconvolution with Condat-Vu.

Perform deconvolution using sparse regularisation with the Condat-Vu algorithm.

Parameters

• data (numpy.ndarray) – Input data, 2D image

• psf (numpy.ndarray) – Input PSF, 2D image

• n_iter (int, optional) – Maximum number of iterations, default is 300

• n_reweights (int, optional) – Number of reweightings, default is 1

• verbose (bool, optional) – Verbosity option, default is True

• progress (bool, optional) – Option to show progress bar, default is True

Returns

Deconvolved image

Return type

numpy.ndarray