/image-processing-from-scratch

This project contains some interesting image processing algorithms that were wrote in python and c++ from scratch.

Primary LanguageC++MIT LicenseMIT

image processing from scratch

what is this?

This repository contains many interesting image processing algorithms that are written from scratch. Read these codes will allow you to have a comprehensive understanding of the principles of these algorithms. I also have video tutorials for these algorithms here. Go check out if you know Chinese :-)

Implementation
All codes were wrote in python3.7 or c++
moudles you may need:
python:

  • numpy for matix calculation
  • matplotlib for reading and showing images
  • opencv2 for some image operations

c++:

  • opencv2

Usage
you can always run a python script just by
python script.py

for c++, you need to compile first
cd build
cmake ..
make

when it's done, you are ready to run the executable file by
./program_name parameters
Just make sure you have the images in the right path, and you might wanna modify the code a bit to process another image.
Have fun!

Contents

  • canny edge detection
    It is an algorithm that extracts edges of an image.

  • hough transform
    It is an algorithm that can theoratically detects shapes that you can write formulas for it.

  • harris corner detection
    This algorithm detects corners.

  • fast fourier transform
    2-D fourier transform for images using fft.

  • sift
    Scale-invariant feature transform, a well-known technique to extract feature points for image matching. Now added c++ version along with SURF and ORB.

  • KNN
    Using balanced K-D tree to find k nearest neighbors of K-dimension points.

  • PCA&SVD
    Do PCA and SVD using jacobi rotation.(which is accurate but slow)

  • Ransac
    Stitch different images together after knowing the sift keypoint pairs.

  • watershed
    watershed segmentation algorithm.

  • meanshift
    meanshift segmentation algorithm.

  • generalized hough transform
    template match of images, detects a given template in an query image. The vote space is implemented with a sparse vector to support big images.

  • closed-form image matting
    a classic image matting algorithm proposed in A Closed-Form Solution to Natural Image Matting

  • haze removal
    Using dark channel prior and fast guided filter proposed in Single Image Haze Removal Using Dark Channel Prior and Fast Guided Filter

  • a lot to be continued...