pylops.signalprocessing.DWT2D

class pylops.signalprocessing.DWT2D(dims, dirs=(0, 1), wavelet='haar', level=1, dtype='float64')

Two dimensional Wavelet operator.

Apply 2D-Wavelet Transform along two directions dirs of a multi-dimensional array of size dims.

Note that the Wavelet operator is an overload of the pywt implementation of the wavelet transform. Refer to https://pywavelets.readthedocs.io for a detailed description of the input parameters.

Parameters:

dims : tuple

Number of samples for each dimension

dirs : tuple, optional

Direction along which DWT2D is applied.

wavelet : str, optional

Name of wavelet type. Use pywt.wavelist(kind='discrete') for a list of available wavelets.

level : int, optional

Number of scaling levels (must be >=0).

dtype : str, optional

Type of elements in input array.

Raises:

ModuleNotFoundError

If pywt is not installed

ValueError

If wavelet does not belong to pywt.families

Notes

The Wavelet operator applies the 2-dimensional multilevel Discrete Wavelet Transform (DWT2) in forward mode and the 2-dimensional multilevel Inverse Discrete Wavelet Transform (IDWT2) in adjoint mode.

Attributes:

shape : tuple

Operator shape

explicit : bool

Operator contains a matrix that can be solved explicitly (True) or not (False)

Methods

__init__(dims[, dirs, wavelet, level, dtype])	Initialize this LinearOperator.
adjoint()	Hermitian adjoint.
apply_columns(cols)	Apply subset of columns of operator
cond([uselobpcg])	Condition number of linear operator.
conj()	Complex conjugate operator
div(y[, niter, densesolver])	Solve the linear problem \(\mathbf{y}=\mathbf{A}\mathbf{x}\).
dot(x)	Matrix-matrix or matrix-vector multiplication.
eigs([neigs, symmetric, niter, uselobpcg])	Most significant eigenvalues of linear operator.
matmat(X)	Matrix-matrix multiplication.
matvec(x)	Matrix-vector multiplication.
rmatmat(X)	Matrix-matrix multiplication.
rmatvec(x)	Adjoint matrix-vector multiplication.
todense([backend])	Return dense matrix.
toimag([forw, adj])	Imag operator
toreal([forw, adj])	Real operator
tosparse()	Return sparse matrix.
trace([neval, method, backend])	Trace of linear operator.
transpose()	Transpose this linear operator.

Examples using pylops.signalprocessing.DWT2D

Wavelet transform

05. Image deblurring