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# Sigproc function

Bilateral is a noise reduction function.

See the file `test_pwc.py` for an example.

## bilateral

`sigproc.``bilateral`(y, soft, beta, width, display=1, stoptol=1.0, maxiter=50)

  Performs PWC denoising of the input signal using hard or soft kernel bilateral filtering.

  Parameters:
    y: numpy array
      Original signal to denoise of length N.
    soft: int
      Set this to 1 to use the soft Gaussian kernel, else uses the hard kernel.
    beta: int
      Kernel parameter. If soft Gaussian kernel, then this is the precision parameter. If hard kernel, this is the kernel support.
    width: int
      Spatial kernel width W.
    display: int [default 1]
      Set to 0 to turn off progress display, 1 to turn on. If not specifed, defaults to progress display on.
    stoptol: float [default 1**-3]
      Precision of estimate as determined by square magnitude of the change in the solution. If not specified, defaults to 1e-3.
    maxiter: int [default 50]
      Maximum number of iterations. If not specified, defaults to 50.
  Results: numpy array
    Denoised output signal.
  Reference:

    (c) Max Little, 2011. If you use this code for your research, please cite: M.A. Little, Nick S. Jones (2011) “Generalized Methods and Solvers for Noise Removal from Piecewise Constant Signals: Part I and II” Proceedings of the Royal Society A (in press).

    See http://www.maxlittle.net/

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