# pylops.signalprocessing.DWT2D#

class pylops.signalprocessing.DWT2D(dims, axes=(-2, -1), wavelet='haar', level=1, dtype='float64', name='D')[source]#

Two dimensional Wavelet operator.

Apply 2D-Wavelet Transform along two axes 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
dimstuple

Number of samples for each dimension

axesint, optional

New in version 2.0.0.

Axis along which DWT2D is applied

waveletstr, optional

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

levelint, optional

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

dtypestr, optional

Type of elements in input array.

namestr, optional

New in version 2.0.0.

Name of operator (to be used by pylops.utils.describe.describe)

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
shapetuple

Operator shape

explicitbool

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

Methods

 __init__(dims[, axes, wavelet, level, ...]) 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. reset_count() Reset counters 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()

## Examples using pylops.signalprocessing.DWT2D#

Wavelet transform

Wavelet transform

05. Image deblurring

05. Image deblurring