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# make_lupton_rgb

astropy.visualization.make_lupton_rgb(image_r, image_g, image_b, interval=None, stretch_object=None, minimum=None, stretch=5, Q=8, filename=None, output_dtype=<class 'numpy.uint8'>)

  Return a Red/Green/Blue color image from 3 images using interconnected band scaling, and an arbitrary stretch function (by default, an asinh stretch). The input images can be int or float, and in any range or bit-depth.

  For a more detailed look at the use of this method, see the document Creating color RGB images.

  Parameters:
    image_r `ndarray`

      Image to map to red.

    image_g `ndarray`

      Image to map to green.

    image_b `ndarray`

      Image to map to blue.

    interval `BaseInterval` subclass instance or numpy:array_like, optional

      The interval object to apply to the data (either a single instance or an array for R, G, B). Default is `ManualInterval` with vmin=0.

    stretch_object `BaseStretch` subclass instance, optional

      The stretch object to apply to the data. If set, the input values of `minimum`, `stretch`, and `Q` will be ignored. For the Lupton scheme, this would be an instance of `LuptonAsinhStretch`, but alternatively `LuptonAsinhZscaleStretch` or some other stretch can be used.

    minimum `python:float` or numpy:array_like, optional

      Deprecated. Intensity that should be mapped to black (a scalar or array of R, G, B). If `None`, each image’s minimum value is used. Default is None.

    stretch `python:float`, optional

      The linear stretch of the image. Default is 5

    Q `python:float`, optional

      The asinh softening parameter. Default is 8.

    filename `python:str`, optional

      Write the resulting RGB image to a file (file type determined from extension).

    output_dtype `numpy` scalar type, optional

      Image output data type. Default is np.uint8.

  Returns:
    rgb `ndarray`

      RGB color image as an NxNx3 numpy array, with the specified data type format