Chapter 5. Image Enhancement Using Derivatives

In this chapter, we shall continue our discussion on image enhancement, which is the problem of improving the appearance or usefulness of an image. We shall concentrate mainly on spatial filtering techniques to compute image gradients/derivatives, and how these techniques can be used for edge detection in an image. First, we shall start with the basic concepts of image gradients using the first order (partial) derivatives, how to compute the discrete derivatives, and then discuss the second order Derivative/Laplacian. We shall see how they can be used to find edges in an image. Next, we shall discuss a few ways to sharpen/unsharp mask an image using the Python image processing librariesPIL, the filter module of scikit-image, and thendimage module of SciPy. Next, we shall see how to use different filters (sobel, canny, LoG, and so on) and convolve them with the image to detect edges in an image. Finally, we shall discuss how to compute Gaussian...