# Discrete Wavelet Transform (DWT)

Wavelet transform has recently become a very popular when it comes to analysis, de-noising and compression of signals and images. This section describes functions used to perform single- and multilevel Discrete Wavelet Transforms.

## Single level `dwt`

See the signal extension modes section for the list of available options and the `dwt_coeff_len()` function for information on getting the expected result length.

The transform can be performed over one axis of multi-dimensional data. By default this is the last axis. For multi-dimensional transforms see the 2D transforms section.

## Multilevel decomposition using `wavedec`

## Partial Discrete Wavelet Transform data decomposition `downcoef`

## Maximum decomposition level - `dwt_max_level`

## Result coefficients length - `dwt_coeff_len`

Based on the given input data length (`data_len`), wavelet decomposition filter length (`filter_len`) and signal extension mode, the `dwt_coeff_len()` function calculates the length of the resulting coefficients arrays that would be created while performing `dwt()` transform.

`filter_len` can be either an `int` or `Wavelet` object for convenience.