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Site Navigation

  • User guide
  • Examples
  • API reference
  • Release notes
  • Development
  • About
  • GitHub
  • PyPI

Section Navigation

  • Data
    • Datasets with 3 or more spatial dimensions
    • Scientific images
    • General-purpose images
    • Specific images
  • Operations on NumPy arrays
    • Using simple NumPy operations for manipulating images
    • Generate footprints (structuring elements)
    • Block views on images/arrays
    • Decompose flat footprints (structuring elements)
  • Manipulating exposure and color channels
    • RGB to grayscale
    • RGB to HSV
    • Histogram matching
    • Adapting gray-scale filters to RGB images
    • Separate colors in immunohistochemical staining
    • Filtering regional maxima
    • Gamma and log contrast adjustment
    • Histogram Equalization
    • Tinting gray-scale images
    • Local Histogram Equalization
    • 3D adaptive histogram equalization
  • Edges and lines
    • Contour finding
    • Convex Hull
    • Canny edge detector
    • Marching Cubes
    • Ridge operators
    • Active Contour Model
    • Shapes
    • Random Shapes
    • Approximate and subdivide polygons
    • Straight line Hough transform
    • Circular and Elliptical Hough Transforms
    • Skeletonize
    • Edge operators
  • Geometrical transformations and registration
    • Swirl
    • Interpolation: Edge Modes
    • Rescale, resize, and downscale
    • Build image pyramids
    • Piecewise Affine Transformation
    • Using geometric transformations
    • Structural similarity index
    • Types of homographies
    • Fundamental matrix estimation
    • Robust line model estimation using RANSAC
    • Radon transform
    • Robust matching using RANSAC
  • Image registration
    • Image Registration
    • Masked Normalized Cross-Correlation
    • Registration using optical flow
    • Assemble images with simple image stitching
    • Using Polar and Log-Polar Transformations for Registration
  • Filtering and restoration
    • Removing small objects in grayscale images with a top hat filter
    • Hysteresis thresholding
    • Image Deconvolution
    • Using window functions with images
    • Unsharp masking
    • Mean filters
    • Image Deconvolution
    • Estimate strength of blur
    • Entropy
    • Calibrating Denoisers Using J-Invariance
    • Fill in defects with inpainting
    • Band-pass filtering by Difference of Gaussians
    • Denoising a picture
    • Shift-invariant wavelet denoising
    • Phase Unwrapping
    • Non-local means denoising for preserving textures
    • Attribute operators
    • Wavelet denoising
    • Butterworth Filters
    • Full tutorial on calibrating Denoisers Using J-Invariance
  • Detection of features and objects
    • Dense DAISY feature description
    • Histogram of Oriented Gradients
    • Template Matching
    • Filling holes and finding peaks
    • CENSURE feature detector
    • Corner detection
    • Multi-Block Local Binary Pattern for texture classification
    • Haar-like feature descriptor
    • Blob Detection
    • ORB feature detector and binary descriptor
    • Gabors / Primary Visual Cortex “Simple Cells” from an Image
    • Fisher vector feature encoding
    • BRIEF binary descriptor
    • SIFT feature detector and descriptor extractor
    • GLCM Texture Features
    • Shape Index
    • Sliding window histogram
    • Gabor filter banks for texture classification
    • Local Binary Pattern for texture classification
  • Segmentation of objects
    • Region Boundary based RAGs
    • RAG Thresholding
    • Normalized Cut
    • Find Regular Segments Using Compact Watershed
    • Thresholding
    • Drawing Region Adjacency Graphs (RAGs)
    • Chan-Vese Segmentation
    • Finding local maxima
    • Niblack and Sauvola Thresholding
    • Multi-Otsu Thresholding
    • Apply maskSLIC vs SLIC
    • Random walker segmentation
    • Expand segmentation labels without overlap
    • Watershed segmentation
    • Label image regions
    • Markers for watershed transform
    • Comparison of segmentation and superpixel algorithms
    • Find the intersection of two segmentations
    • Region Adjacency Graphs
    • Measure perimeters with different estimators
    • RAG Merging
    • Hierarchical Merging of Region Boundary RAGs
    • Extrema
    • Explore and visualize region properties with pandas
    • Hausdorff Distance
    • Measure region properties
    • Trainable segmentation using local features and random forests
    • Morphological Snakes
    • Flood Fill
    • Euler number
    • Evaluating segmentation metrics
    • Use rolling-ball algorithm for estimating background intensity
  • Longer examples and demonstrations
    • Render text onto an image
    • Face detection using a cascade classifier
    • Interact with 3D images (of kidney tissue)
    • Use pixel graphs to find an object’s geodesic center
    • Visual image comparison
    • Morphological Filtering
    • Estimate anisotropy in a 3D microscopy image
    • Comparing edge-based and region-based segmentation
    • Colocalization metrics
    • Segment human cells (in mitosis)
    • Thresholding
    • Restore spotted cornea image with inpainting
    • Track solidification of a metallic alloy
    • Measure fluorescence intensity at the nuclear envelope
    • Face classification using Haar-like feature descriptor
    • Explore 3D images (of cells)
    • Rank filters
  • Examples for developers
    • Li thresholding
    • Max-tree
  • Examples
  • Operations...

Operations on NumPy arrays#

Using simple NumPy operations for manipulating images

Using simple NumPy operations for manipulating images

Generate footprints (structuring elements)

Generate footprints (structuring elements)

Block views on images/arrays

Block views on images/arrays

Decompose flat footprints (structuring elements)

Decompose flat footprints (structuring elements)
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