frei_ampfrei_ampFreiAmpFreiAmpfrei_amp (算子名称)
名称
frei_ampfrei_ampFreiAmpFreiAmpfrei_amp — Detect edges (amplitude) using the Frei-Chen operator.
参数签名
def frei_amp(image: HObject) -> HObject
描述
frei_ampfrei_ampFreiAmpFreiAmpFreiAmpfrei_amp calculates an approximation of the first
derivative of the image data and is used as an edge detector. The
filter is based on the following filter masks:
A =
1 sqrt(2) 1
0 0 0
-1 -sqrt(2) -1
B =
1 0 -1
sqrt(2) 0 -sqrt(2)
1 0 -1
The result image contains the maximum response of the masks A and
B.
注意
Note that filter operators may return unexpected results if
an image with a reduced domain is used as input. Please refer to the
chapter 过滤器.
运行信息
- 多线程类型:可重入(与非独占操作符并行运行)。
- 多线程作用域:全局(可以从任何线程调用)。
- 在元组级别自动并行化。
- 在图像通道级别自动并行化。
- Automatically parallelized on domain level.
参数表
ImageImageImageImageimageimage (input_object) (multichannel-)image(-array) → objectHImageHObjectHImageHobject (byte / int2 / uint2)
Input image.
ImageEdgeAmpImageEdgeAmpImageEdgeAmpImageEdgeAmpimageEdgeAmpimage_edge_amp (output_object) (multichannel-)image(-array) → objectHImageHObjectHImageHobject * (byte / int2 / uint2)
Edge amplitude (gradient magnitude) image.
例程 (HDevelop)
read_image(Image,'fabrik')
frei_amp(Image,Frei_amp)
threshold(Frei_amp,Edges,128,255)
例程 (C)
read_image(&Image,"fabrik");
frei_amp(Image,&Frei_amp);
threshold(Frei_amp,&Edges,128,255);
例程 (HDevelop)
read_image(Image,'fabrik')
frei_amp(Image,Frei_amp)
threshold(Frei_amp,Edges,128,255)
例程 (HDevelop)
read_image(Image,'fabrik')
frei_amp(Image,Frei_amp)
threshold(Frei_amp,Edges,128,255)
例程 (HDevelop)
read_image(Image,'fabrik')
frei_amp(Image,Frei_amp)
threshold(Frei_amp,Edges,128,255)
结果
frei_ampfrei_ampFreiAmpFreiAmpFreiAmpfrei_amp always returns 2 (
H_MSG_TRUE)
. If the input is empty
the behavior can be set via
set_system('no_object_result',<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)set_system("no_object_result",<Result>).
如有必要,将引发异常。
可能的前置算子
binomial_filterbinomial_filterBinomialFilterBinomialFilterBinomialFilterbinomial_filter,
gauss_filtergauss_filterGaussFilterGaussFilterGaussFiltergauss_filter,
sigma_imagesigma_imageSigmaImageSigmaImageSigmaImagesigma_image,
median_imagemedian_imageMedianImageMedianImageMedianImagemedian_image,
smooth_imagesmooth_imageSmoothImageSmoothImageSmoothImagesmooth_image
可替代算子
sobel_ampsobel_ampSobelAmpSobelAmpSobelAmpsobel_amp,
kirsch_ampkirsch_ampKirschAmpKirschAmpKirschAmpkirsch_amp,
prewitt_ampprewitt_ampPrewittAmpPrewittAmpPrewittAmpprewitt_amp,
robinson_amprobinson_ampRobinsonAmpRobinsonAmpRobinsonAmprobinson_amp,
robertsrobertsRobertsRobertsRobertsroberts
参考其它
bandpass_imagebandpass_imageBandpassImageBandpassImageBandpassImagebandpass_image,
laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGaussLaplaceOfGausslaplace_of_gauss
模块
Foundation