Historical Image Pre-Processing
Project description
hipp
HIPP (Historical Image Pre-Processing) is a python library to pre-process scanned historical images for Structure from Motion surface reconstruction and photogrammetric analysis.
Features
Preprocessing of Aerial Images
-
Fiducial Marker Detection
- Built-in application to generate fiducial marker templates
- Detection of fiducial marker coordinates using OpenCV template matching
- Sub-pixel accuracy for fiducial detection
- Supports detection of 4 midside and/or 4 corner fiducials
- Replaces low-confidence matches with
None, based on a matching score threshold - Estimates the principal point based on valid fiducials
- Quality Control Outputs:
- Cropped windows around detected fiducials for visual inspection
- Distribution plots of principal point deviations and individual fiducial coordinates
- Matching score distributions
- RMSE of fiducial coordinates before and after affine transformation
-
Fiducial Marker Proxy Detection (feature in development)
-
Image Restitution
- Computes the appropriate geometric transformation between detected and calibrated fiducial positions:
- 1 point → Translation
- 2 points → Similarity transformation
- 3+ points → Affine transformation
- Crops the image around the estimated principal point to a standard size
- Applies CLAHE (Contrast Limited Adaptive Histogram Equalization) to enhance features for SfM (Structure from Motion)
- Computes the full affine transformation matrix (including crop transformation)
- Computes the appropriate geometric transformation between detected and calibrated fiducial positions:
See this notebook for example.
Preprocessing of KH-9 Panoramic Camera Satellite Images
-
Image Joining
- Joins split images into a single composite image
- Requires input images named sequentially (e.g.
ImageId_a,ImageId_b,ImageId_c, …) - A small overlap between image parts is required for proper stitching
- Uses
image_mosaicfrom the ASP toolkit
-
Image Cropping
- Built-in interactive tool to manually select corners of the region of interest
- Rotates and crops the image to align the selected top edge horizontally
See this notebook for example.
Preprocessing of KH-9 Mapping Camera Satellite Images (feature in development)
Installation
This pipeline requires the ASP toolkit to be installed and accessible in your system's PATH.
Steps to install the ASP toolkit (2025-06-22 daily build)
# Navigate to your home directory
cd ~
# Download the 2025-06-22 daily build of the ASP toolkit
wget https://github.com/NeoGeographyToolkit/StereoPipeline/releases/download/2025-06-22-daily-build/StereoPipeline-3.6.0-alpha-2025-06-22-x86_64-Linux.tar.bz2
# Extract the downloaded archive
tar xvf StereoPipeline-3.6.0-alpha-2025-06-22-x86_64-Linux.tar.bz2
# (Optional) Remove the archive to free up space
rm -f StereoPipeline-3.6.0-alpha-2025-06-22-x86_64-Linux.tar.bz2
# To permanently add the ASP executable subdirectory to your PATH, add to your shell configuration (e.g., ~/.bashrc), a line similar to:
export PATH="${PATH}":"$HOME/StereoPipeline-3.6.0-alpha-2025-06-22-x86_64-Linux/bin"
After completing these steps, verify that the ASP toolkit is correctly installed and accessible by running:
which stereo
Installing hipp
Once the ASP toolkit is properly installed and available in your PATH, you can install hipp using pip:
pip install hipp
License
hipp is distributed under the terms of the Apache-2.0 license.
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