tessl/pypi-itk

Insight Toolkit for N-dimensional image processing, segmentation, and registration in medical and scientific applications

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Thresholding

Name: tessl/pypi-itk
Author: tessl

Threshold images using various methods including manual thresholding and automatic threshold selection algorithms.

Capabilities

Basic Thresholding

def binary_threshold_image_filter(input, lower_threshold=0, upper_threshold=255, inside_value=1, outside_value=0):
    """
    Binary threshold with specified range.
    
    Parameters:
    - input: itk.Image - Input image
    - lower_threshold: pixel_type - Lower bound of threshold range
    - upper_threshold: pixel_type - Upper bound of threshold range
    - inside_value: pixel_type - Output value for pixels in range
    - outside_value: pixel_type - Output value for pixels outside range
    
    Returns:
    itk.Image - Binary thresholded image
    """

def threshold_image_filter(input, lower=0, upper=255, outside_value=0):
    """
    Threshold image in-place (pixels outside range set to outside_value).
    
    Parameters:
    - input: itk.Image - Input image
    - lower: pixel_type - Lower threshold
    - upper: pixel_type - Upper threshold
    - outside_value: pixel_type - Value for pixels outside range
    
    Returns:
    itk.Image - Thresholded image
    """

Automatic Threshold Selection

def otsu_threshold_image_filter(input, inside_value=1, outside_value=0, number_of_histogram_bins=128):
    """
    Otsu's automatic threshold selection method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    - number_of_histogram_bins: int - Number of histogram bins
    
    Returns:
    itk.Image - Binary thresholded image
    """

def otsu_multiple_thresholds_image_filter(input, number_of_thresholds=1, number_of_histogram_bins=128):
    """
    Multi-level Otsu thresholding.
    
    Parameters:
    - input: itk.Image - Input image
    - number_of_thresholds: int - Number of thresholds to compute
    - number_of_histogram_bins: int - Number of histogram bins
    
    Returns:
    itk.Image - Multi-level labeled image
    """

def huang_threshold_image_filter(input, inside_value=1, outside_value=0):
    """
    Huang's fuzzy thresholding method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    
    Returns:
    itk.Image - Binary thresholded image
    """

def li_threshold_image_filter(input, inside_value=1, outside_value=0):
    """
    Li's iterative minimum cross entropy method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    
    Returns:
    itk.Image - Binary thresholded image
    """

def yen_threshold_image_filter(input, inside_value=1, outside_value=0):
    """
    Yen's threshold method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    
    Returns:
    itk.Image - Binary thresholded image
    """

def renyi_entropy_threshold_image_filter(input, inside_value=1, outside_value=0):
    """
    Renyi entropy threshold method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    
    Returns:
    itk.Image - Binary thresholded image
    """

def triangle_threshold_image_filter(input, inside_value=1, outside_value=0):
    """
    Triangle threshold method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    
    Returns:
    itk.Image - Binary thresholded image
    """

def moments_threshold_image_filter(input, inside_value=1, outside_value=0):
    """
    Moments-based threshold method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    
    Returns:
    itk.Image - Binary thresholded image
    """

def kittler_illingworth_threshold_image_filter(input, inside_value=1, outside_value=0):
    """
    Kittler-Illingworth threshold method.
    
    Parameters:
    - input: itk.Image - Input image
    - inside_value: pixel_type - Output value for foreground
    - outside_value: pixel_type - Output value for background
    
    Returns:
    itk.Image - Binary thresholded image
    """

Usage Examples

Basic Binary Thresholding

import itk

image = itk.imread('input.png', itk.UC)

# Threshold to binary
binary = itk.binary_threshold_image_filter(
    image,
    lower_threshold=100,
    upper_threshold=255,
    inside_value=255,
    outside_value=0
)
itk.imwrite(binary, 'binary.png')

Otsu's Automatic Thresholding

import itk

image = itk.imread('input.png', itk.UC)

# Automatic threshold using Otsu's method
binary = itk.otsu_threshold_image_filter(
    image,
    inside_value=255,
    outside_value=0
)
itk.imwrite(binary, 'otsu.png')

# Multi-level Otsu
multilevel = itk.otsu_multiple_thresholds_image_filter(
    image,
    number_of_thresholds=2  # Creates 3 classes
)
itk.imwrite(multilevel, 'multilevel.png')

Comparing Threshold Methods

import itk

image = itk.imread('input.png', itk.UC)

methods = {
    'otsu': itk.otsu_threshold_image_filter,
    'huang': itk.huang_threshold_image_filter,
    'li': itk.li_threshold_image_filter,
    'yen': itk.yen_threshold_image_filter,
    'triangle': itk.triangle_threshold_image_filter,
    'moments': itk.moments_threshold_image_filter,
}

for name, method in methods.items():
    result = method(image, inside_value=255, outside_value=0)
    itk.imwrite(result, f'{name}_threshold.png')

Install with Tessl CLI

npx tessl i tessl/pypi-itk