In this chapter, we will cover the following recipes:
- Manipulating matrices-creating, filling, accessing elements, and ROIs
- Converting between different data types and scaling values
- Non-image data persistence using NumPy
- Manipulating image channels
- Converting images from one color space to another
- Gamma correction and per-element math
- Mean/variance image normalization
- Computing image histograms
- Equalizing image histograms
- Removing noise using Gaussian, median, and bilateral filters
- Computing gradient images using Sobel filters
- Creating and applying your own filter
- Processing images with real-valued Gabor filters
- Going from the spatial to the frequency domain (and back) using discrete Fourier transform
- Manipulating ...
