fluidimage.works.preproc._toolbox_py

Preprocess toolbox

A toolbox for preprocessing images. Utilizes functions available from scipy.ndimage and skimage packages. cf. http://www.scipy-lectures.org/advanced/image_processing/

Provides:

members:

Functions

adaptive_threshold([img, window_size, offset])	Adaptive threshold transforms a grayscale image to a binary image.
equalize_hist_adapt([img, window_shape, nbins])	Contrast Limited Adaptive Histogram Equalization (CLAHE).
equalize_hist_global([img, nbins])	Increases global contrast of the image.
equalize_hist_local([img, radius])	Adaptive histogram equalization (AHE) emphasizes every local graylevel variations [1].
gamma_correction([img, gamma, gain])	Gamma correction or power law transform.
global_threshold([img, minima, maxima])	Trims pixel intensities which are outside the interval (minima, maxima).
imstats(img[, hist_bins])
rescale_intensity([img, minima, maxima])	Rescale image intensities, between the specified minima and maxima, by using a multiplicative factor.
rescale_intensity_tanh([img, threshold])	Rescale image intensities, using a tanh fit.
sharpen([img, sigma1, sigma2, alpha])	Sharpen image edges.
sliding_median([img, weight, window_size, ...])	Subtracts the median calculated within a sliding window from the centre of the window.
sliding_minima([img, weight, window_size, ...])	Subtracts the minimum calculated within a sliding window from the centre of the window.
sliding_percentile([img, percentile, ...])	Flexible version of median filter.
temporal_median([img, weight, window_shape])	Subtracts the median calculated in time and space, for each pixel.
temporal_minima([img, weight, window_shape])	Subtracts the minima calculated in time and space, for each pixel.
temporal_percentile([img, percentile, ...])	Flexible version of median filter.