The objective of image enhancement is to improve the quality of an image or make particular features appear more prominent. The techniques used are often more general-purpose techniques and a strong model of the degradation process is not assumed (unlike image restoration, which we will see in the next chapter). Some examples of image enhancement techniques are denoising/smoothing (using different classical image processing, unsupervised machine learning, and deep learning techniques), contrast improvement, and sharpening.
In this chapter, we will cover the following recipes for image enhancement (and their implementations using Python libraries):
- Applying filters to denoise different types of noise in an image
- Image denoising with a denoising autoencoder
- Image denoising with PCA/DFT/DWT
- Image denoising with anisotropic diffusion
- Improving image contrast with...
