GSoC 2020

Google Summer of Code 2020

This is list of proposals of GIL projects for GSoC 2020. The projects below are also copied to the official Boost wiki at https://github.com/boostorg/wiki/wiki/Google-Summer-of-Code%3A-2020 where all Boost proposals are collected.

PROJECT 1: Image Processing Algorithms

This proposal is continuation of Image Processing Algorithms project submitted and developed by Miral Shah during GSoC 2019.

Boost.GIL provides core features for images and, thanks to Miral Shah's work, a collection of basic image processing algorithms. However, there still is more algorithms to be added to the collection.

Check GIL's wiki page Image Processing Algorithms with table presenting the algorithms implementation status and the wish-list.

1. Mathematical Morphology

• Dilation
• Erosion
• Blurring / Smoothing
• Sharpening

2. Normalizing Channels

3. De-Noising

• Wiener filter
• Average filter
• Median filter

4. Kernels and Convolutions

• The GSoC 2019 project implemented lots of improvements and new features in the kernels and convolutions, but this area may still benefit from further development, optimisations and documenting.

5. Your favourite image processing algorithms

6. Image Processing Documentation

• We need a beautifully written and presented documentation of the image processing features in GIL
• For example, https://github.com/boostorg/gil/issues/396, describes an idea of the docs structure based on the "Principles of Digital Image Processing" book

PROJECT 2: Histogram

Histogram is one of essential tools in the image processing techniques. Although it belongs to the image processing algorithms, we propose this as a separate self-contained project.

Although Boost.GIL presents how to compute histogram in the documentation, Tutorial: Histogram, as well some existing algorithms already compute histogram as in case of the Otsu's thresholding, there is no functionality in GIL available via public interfaces for histogram computation and operations.

This project proposal is about making histogram a first-class feature in GIL.

List of suggested topics:

• Computing histograms
  • 1D histogram of single image (8-bit grayscale image)
  • Histograms of images with more than 8 bits (Binning technique)
  • Histogram of color images
    • Intensity histogram (Luminance)
    • Individual color channel histogram
    • Combined color histogram
    • 1D histogram of individual components of any color space of single image (HSV, RGB, XYZ)
    • 2D histogram projections of single image (e.g. H and S of HSV, R and B of RGB, etc.)
    • 3D histogram of single image (e.g. 3D Color Inspector plug-in for ImageJ)
  • Cumulative histogram
• Point operations - histogram transformations or histogram-based image enhancements
  • Histogram Normalization
  • Histogram Equalization
  • Histogram Specification - adjusting an image to a given reference histogram
  • Thresholding - use of new histogram computation in the GIL thresholding algorithms
• Integration with Boost.Histogram
• Histogram visualization - for testing and debugging purposes
  • GIL extension for basic plotting of histogram in SVG format (e.g. see SVG in Boost.Geometry)
  • GIL extension based on a third-party plotting library