radon(image, theta=None, circle=True, *, preserve_range=None)

Notes

Based on code of Justin K. Romberg (https://www.clear.rice.edu/elec431/projects96/DSP/bpanalysis.html)

Parameters

image : array_like

Input image. The rotation axis will be located in the pixel with indices (image.shape[0] // 2, image.shape[1] // 2) .

theta : array_like, optional

Projection angles (in degrees). If :None:None:`None`, the value is set to np.arange(180).

circle : boolean, optional

Assume image is zero outside the inscribed circle, making the width of each projection (the first dimension of the sinogram) equal to min(image.shape) .

preserve_range : bool, optional

Whether to keep the original range of values. Otherwise, the input image is converted according to the conventions of img_as_float . Also see https://scikit-image.org/docs/dev/user_guide/data_types.html

Returns

radon_image : ndarray

Radon transform (sinogram). The tomography rotation axis will lie at the pixel index radon_image.shape[0] // 2 along the 0th dimension of radon_image .

Calculates the radon transform of an image given specified projection angles.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

---

File: /skimage/transform/radon_transform.py#24
type: <class 'function'>
Commit: