Smooth an image using recursive filters.
smooth_image smooths gray images using recursive filters originally developed by Deriche and Shen and using the non-recursive Gaussian filter. The following filters can be choosen via the parameter Filter:
'deriche1', 'deriche2', 'shen' und 'gauss'.
The ``filter width'' (i.e., the range of the filter and thereby
result of the filter) can be of any size. In the case that the
Deriche or Shen is choosen it decreases by increasing the filter
parameter Alpha and increases in the case of the Gauss
filter (and Alpha corresponds to the standard deviation
of the Gaussian function). An approximation of the appropiate size
of the filterwidth Alpha is performed by the operator
info_smooth.
Non-recursive filters like the Gaussian filter are often implemented using filter-masks. In this case the runtime of the operator increases with increasing size of the filter mask. The runtime of the recursive filters remains constant; except the border treatment becomes a little bit more time consuming. The Gaussian filter becomes slow in comparison to the recursive ones but is in contrast to them isotropic (the filter 'deriche2' is only weakly direction sensitive). A comparable result of the smoothing is achieved by choosing the following values for the parameter:
Alpha(deriche2) = Alpha(deriche1) / 2,
Alpha(shen) = Alpha(deriche1) / 2,
Alpha(gauss) = 1.77 / Alpha(deriche1).
|
Image (input_object) |
(multichannel-)image(-array) -> object : byte / uint2 |
| Image to be smoothed. | |
|
ImageSmooth (output_object) |
(multichannel-)image(-array) -> object : byte / uint2 |
| Smoothed image. | |
|
Filter (input_control) |
string -> string |
| Filter. | |
| Default value: 'deriche2' | |
| List of values: 'deriche1', 'deriche2', 'shen', 'gauss' | |
|
Alpha (input_control) |
real -> real |
| Filterparameter: small values cause strong smoothing (vice versa by using bei 'gauss'). | |
| Default value: 0.5 | |
| Suggested values: 0.1, 0.2, 0.3, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 4.0, 5.0, 7.0, 10.0 | |
| Typical range of values: 0.01 <= Alpha <= 50.0 | |
| Minimum increment: 0.01 | |
|
Recommended increment: 0.1 | |
| Restriction: Alpha > 0 | |
info_smooth('deriche2',0.5,Size,Coeffs)
smooth_image(Input,Smooth,'deriche2',7)
If the parameter values are correct the operator smooth_image returns the value 2 (H_MSG_TRUE). The behavior in case of empty input (no input images available) is set via the operator set_system('no_object_result',<Result>). If necessary an exception handling is raised.
smooth_image is reentrant and automatically parallelized (on tuple level, channel level).
threshold, dyn_threshold, regiongrowing
gauss_image, mean_image, derivate_gauss
info_smooth, median_image, sigma_image, anisotrope_diff
R.Deriche: ``Fast Algorithms for Low-Level Vision''; IEEE Transactions on Pattern Analysis and Machine Intelligence; PAMI-12, no. 1; S. 78-87; 1990.
Image filters
