Learning OpenCV 3

Chapter 11. General Image Transforms

Overview

In the previous chapters, we covered the class of image transformations that can be understood specifically in terms of convolution. Of course, there are a lot of useful operations that cannot be expressed in this way (i.e., as a little window scanning over the image doing one thing or another). In general, transformations that can be expressed as convolutions are local, meaning that even though they may change the entire image, the effect on any particular pixel is determined by only a small number of pixels around it. The transforms we will look at in this chapter generally will not have this property.

Some very useful image transforms are simple, and you will use them all the time—resize, for example. Others are for more specialized purposes. The image transforms we will look at in this chapter convert one image into another. The output image will often be a different size as the input, or will differ in other ways, but it will still be in essence “a picture” in the same sense as the input. In Chapter 12, we will consider operations that render images into some potentially entirely different representation.

There are a number of useful transforms that arise repeatedly in computer vision. OpenCV provides complete implementations of some of the more common ones as well as building blocks to help you implement your own, more complex, transformations.

Stretch, Shrink, Warp, and Rotate

The simplest image transforms we will encounter ...