Mastering Computer Vision with TensorFlow 2.x

Image sharpening

In image sharpening, the low-frequency noise from an image is removed by applying a high-pass filter (difference operator), which results in the line structure and edges becoming more visible. Image sharpening is also known as a Laplace operation, which is represented by the second derivative, shown here:

Because of the difference operator, the four adjacent cells relative to the midpoint of the kernel always have opposite signs. So, if the midpoint of the kernel is positive, the four adjacent cells are negative, and vice versa. Let's take a look at the following example:

Note that the advantage of the second-order derivative ...