k-Wave Toolbox |

# smooth

Smooth a matrix

## Syntax

    mat_sm = smooth(kgrid, mat)
    mat_sm = smooth(kgrid, mat, restore_max)
    mat_sm = smooth(kgrid, mat, [], window_type)
    mat_sm = smooth(kgrid, mat, restore_max, window_type)

## Description

`smooth` filters an input matrix using an n-dimensional frequency domain window created using `getWin`. If no window type is specified, a Blackman window is used.

## Inputs

`kgrid` | grid structure returned by `makeGrid`
`mat` | spatial distribution to smooth

## Optional Inputs

`restore_max` | Boolean controlling whether the maximum value is restored after smoothing (default = `false`)
`window_type` | shape of the smoothing window; any valid inputs to `getWin` are supported (default = `'Blackman'`)

## Outputs

`mat_sm` | smoothed spatial distribution

## Examples

- 2D FFT Reconstruction For A Line Sensor
- 3D FFT Reconstruction For A Planar Sensor
- 2D Time Reversal For A Line Sensor
- 2D Time Reversal For A Circular Sensor
- 3D Time Reversal For A Planar Sensor
- 3D Time Reversal For A Spherical Sensor
- Image Reconstruction With Directional Sensors
- Image Reconstruction With Bandlimited Sensors
- Image Reconstruction With Compensation For Acoustic Absorption
- Source Smoothing
- Filtering A Delta Function Input Signal
- Modelling Power Law Absorption

## See Also

`fft`, `ifft`, `fft2`, `ifft2`, `fftn`, `ifftn`, `makeGrid`

© 2009, 2010 Bradley Treeby and Ben Cox.