Approximate the LoG operator (Laplace of Gaussian).
diff_of_gauss approximates the Laplace-of-Gauss operator by a difference of Gaussians. The standard deviations of these Gaussians can be calculated, according to Marr, from the Parameter Sigma of the LoG and the ratio of the two standard deviations (SigFactor) as:
sigma1 = Sigma /
sqrt(-2.0 * log {1.0/SigFactor} / (SigFactor^2 - 1.0))
sigma2 = sigma1 / SigFactor
Result = { Object * gauss(sigma1) } - { Object * gauss(sigma2) }
For a SigFactor = 1.6, according
to Marr, an approximation to the Mexican-Hat-Operator results. The
resulting image is stored in DiffOfGauss.
|
Image (input_object) |
(multichannel-)image(-array) -> object : byte |
| Input image | |
|
DiffOfGauss (output_object) |
(multichannel-)image(-array) -> object : int2 |
| LoG image. | |
|
Sigma (input_control) |
real -> real |
| Smoothing parameter of the Laplace operator to approximate. | |
| Default value: 3.0 | |
| Suggested values: 2.0, 3.0, 4.0, 5.0 | |
| Typical range of values: 0.2 <= Sigma <= 50.0 | |
| Minimum increment: 0.01 | |
|
Recommended increment: 0.1 | |
| Restriction: Sigma > 0.0 | |
|
SigFactor (input_control) |
real -> real |
| Ratio of the standard deviations used (Marr recommends 1.6). | |
| Default value: 1.6 | |
| Typical range of values: 0.1 <= SigFactor <= 10.0 | |
| Minimum increment: 0.01 | |
|
Recommended increment: 0.1 | |
| Restriction: SigFactor > 0.0 | |
read_image(Image,'fabrik') diff_of_gauss(Image,Laplace,2.0,1.6) zero_crossing(Laplace,ZeroCrossings).
The execution time depends linearly on the number of pixels and the size of sigma.
diff_of_gauss returns 2 (H_MSG_TRUE) if all parameters are correct. If the input is empty the behaviour can be set via set_system('no_object_result',<Result>). If necessary, an exception handling is raised.
diff_of_gauss is reentrant and automatically parallelized (on tuple level, channel level, domain level).
D. Marr: ``Vision (A computational investigation into human representation and processing of visual information)''; New York, W.H. Freeman and Company; 1982.
Foundation
