This repository serves to explore some image processing topics with Ipython notebooks
Here only the more important Jupyter notebooks are summarized.
(notebooks of lesser importance are those, which have proved useful to study some concepts and programming techniques)
file: corr_and_conv_e.ipynb
review of the concept of correlation applied to image processing. The concept of convolution is only briefly
touched at the end of the notebook. A PDF version corr_and_conv_e.pdf of the notebook is provided for better readability.
file: correlation_convolution_2d_experiments.ipynb
another more detailed review of correlation and convolution applied to 2D images. Moreover the interrelation of correlation and convolution is explained. The OpenCV library has only support for correlation but mentions, that by modification of the kernel (filter) convolution can be computed as well. A PDF version correlation_convolution_2d_experiments.pdf is provided to get a quick overview without having to run the notebook.
file: Fourier_1D_e.ipynb
To familiarize myself with the discrete Fourier transform DFT a reviewed DFT concepts for the 1D case. A PDF version Fourier_1D_e.pdf is also available.
file: Fourier_1D_application_1.ipynb
Some applications of the 1D DFT. Demonstrates how to apply a time shift in the frequency domain and uses Python libraries numpy and scipy. A PDF version Fourier_1D_application_1.pdf is available.
file: fourier_2d.ipynb
reviews properties to the 2D discrete Fourier transform. PDf version: fourier_2d.pdf
file: frequency_domain_filtering.ipynb
how to filter an image in the frequency domain and demonstrating the effect of restricting the bandwidth of the filter. PDF version: frequency_domain_filtering.pdf
file: motion_detection.ipynb
Shows various methods to compare images and proposes a simple method to detect changes in an image (possible application: motion detection). The method is simple but a production quality motion detection schema requires a different approach (eg: extracting features of image1 and image2; then comparing features which a common to both images and which are present in one image but missing in the other ... ). PDF version: motion_detection.pdf
figures, img : some test images