This project contains some interesting image processing algorithms that were wrote in python and c++ from scratch.
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.
Implementation
All codes were wrote in python3.7 or c++
moudles you may need:
python:
c++:
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!
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…