equalize_adapthist skimage.exposure.equalize_adapthist(image, *args, **kwargs) [source] Contrast Limited Adaptive Histogram Equalization (CLAHE). An algorithm for local contrast enhancement, that uses histograms computed over different tile regions of the image. Local details can therefore be enhanced even in regions that are darker or lighter than most of the image. Parameters: image : array-like Input image. kernel_size: integer or 2-tuple Defines the shape of contextual regions used i

equalize skimage.filters.rank.equalize(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source] Equalize image using local histogram. Parameters: image : 2-D array (uint8, uint16) Input image. selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : 2-D array (same dtype as input) If None, a new array is allocated. mask : ndarray Mask array that defines (>0) area of the image included in the local neighborhood. If None, the complete image

entropy skimage.filters.rank.entropy(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source] Local entropy. The entropy is computed using base 2 logarithm i.e. the filter returns the minimum number of bits needed to encode the local greylevel distribution. Parameters: image : 2-D array (uint8, uint16) Input image. selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : 2-D array (same dtype as input) If None, a new array is allocated. mask :

enhance_contrast_percentile skimage.filters.rank.enhance_contrast_percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=0, p1=1) [source] Enhance contrast of an image. This replaces each pixel by the local maximum if the pixel greyvalue is closer to the local maximum than the local minimum. Otherwise it is replaced by the local minimum. Only greyvalues between percentiles [p0, p1] are considered in the filter. Parameters: image : 2-D array (uint8, uint16) Input ima

enhance_contrast skimage.filters.rank.enhance_contrast(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source] Enhance contrast of an image. This replaces each pixel by the local maximum if the pixel greyvalue is closer to the local maximum than the local minimum. Otherwise it is replaced by the local minimum. Parameters: image : 2-D array (uint8, uint16) Input image. selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : 2-D array (same dtyp

ellipsoid_stats skimage.draw.ellipsoid_stats(a, b, c) [source] Calculates analytical surface area and volume for ellipsoid with semimajor axes aligned with grid dimensions of specified spacing. Parameters: a : float Length of semimajor axis aligned with x-axis. b : float Length of semimajor axis aligned with y-axis. c : float Length of semimajor axis aligned with z-axis. Returns: vol : float Calculated volume of ellipsoid. surf : float Calculated surface area of ellipsoid.

ellipsoid skimage.draw.ellipsoid(a, b, c, spacing=(1.0, 1.0, 1.0), levelset=False) [source] Generates ellipsoid with semimajor axes aligned with grid dimensions on grid with specified spacing. Parameters: a : float Length of semimajor axis aligned with x-axis. b : float Length of semimajor axis aligned with y-axis. c : float Length of semimajor axis aligned with z-axis. spacing : tuple of floats, length 3 Spacing in (x, y, z) spatial dimensions. levelset : bool If True, returns the

EllipseModel class skimage.measure.EllipseModel [source] Bases: skimage.measure.fit.BaseModel Total least squares estimator for 2D ellipses. The functional model of the ellipse is: xt = xc + a*cos(theta)*cos(t) - b*sin(theta)*sin(t) yt = yc + a*sin(theta)*cos(t) + b*cos(theta)*sin(t) d = sqrt((x - xt)**2 + (y - yt)**2) where (xt, yt) is the closest point on the ellipse to (x, y). Thus d is the shortest distance from the point to the ellipse. This estimator minimizes the squared distances fr

ellipse_perimeter skimage.draw.ellipse_perimeter() Generate ellipse perimeter coordinates. Parameters: cy, cx : int Centre coordinate of ellipse. yradius, xradius : int Minor and major semi-axes. (x/xradius)**2 + (y/yradius)**2 = 1. orientation : double, optional (default 0) Major axis orientation in clockwise direction as radians. shape : tuple, optional Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for ellipses which exceed th

ellipse skimage.draw.ellipse(r, c, yradius, xradius, shape=None) [source] Generate coordinates of pixels within ellipse. Parameters: r, c : double Centre coordinate of ellipse. yradius, xradius : double Minor and major semi-axes. (x/xradius)**2 + (y/yradius)**2 = 1. shape : tuple, optional Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for ellipses which exceed the image size. By default the full extent of the ellipse are used. R