A series of various image processing algorithms for Fundamentals of Computer Vision course (Fall 2021).
All input images are taken from image processing test collections and Digital Image Processing by R.C. Gonzales and R.E. Woods.
- Affine transformation with bilinear and nearest neighbour interpolation options
- 2-dimensional convolution-based filtering in spatial domain for single and multi band imaged (greyscale, rgb, rgba, etc)
- Fast box filter using dynamic programming (on single and multi band)
- Robert edge detection filters
- Global histogram equalisation
- Fast local histogram localisation using bilinear interpolation
- Unsharp masking for greyscale images using box, weighted avergae, and median filters.
- High-pass and low-pass filtering with FFT.
- Copy-move forgery detection with wavelet transform.
- Image similarity measure with wavelet transform.
- Noise reduction with wavelet transform.