skimage2.feature.multiscale_basic_features

skimage2.feature.multiscale_basic_features(image, intensity=True, edges=True, texture=True, sigma_min=0.5, sigma_max=16, num_sigma=None, workers=None, *, channel_axis=None)

Local features for a single- or multi-channel nd image.

Intensity, gradient intensity and local structure are computed at different scales thanks to Gaussian blurring.

Parameters:

imagendarray

Input image, which can be grayscale or multichannel.

intensitybool, default True

If True, pixel intensities averaged over the different scales are added to the feature set.

edgesbool, default True

If True, intensities of local gradients averaged over the different scales are added to the feature set.

texturebool, default True

If True, eigenvalues of the Hessian matrix after Gaussian blurring at different scales are added to the feature set.

sigma_minfloat, optional

Smallest value of the Gaussian kernel used to average local neighborhoods before extracting features.

sigma_maxfloat, optional

Largest value of the Gaussian kernel used to average local neighborhoods before extracting features.

num_sigmaint, optional

Number of values of the Gaussian kernel between sigma_min and sigma_max. If None, sigma_min multiplied by powers of 2 are used.

workersint or None, optional

The number of parallel threads to use. If set to None, the full set of available cores are used.

channel_axisint or None, optional

If None, the image is assumed to be a grayscale (single channel) image. Otherwise, this parameter indicates which axis of the array corresponds to channels.

Added in version 0.19: channel_axis was added in 0.19.

Returns:

featuresnp.ndarray

Array of shape image.shape + (n_features,). When channel_axis is not None, all channels are concatenated along the features dimension. (i.e. n_features == n_features_singlechannel * n_channels)