Image Pyramids are one of the most beautiful concept of image processing.Normally, we work with images with default resolution but many times we need to change the resolution (lower it) or resize the original image in that case image pyramids comes handy.
pyrUp() function increases the size to double of its original size and
pyrDown() function decreases the size to half. If we keep the original image as a base image and go on applying
pyrDown function on it and keep the images in a vertical stack, it will look like a pyramid. The same is true for upscaling the original image by
Once we scale down and if we rescale it to the original size, we lose some information and the resolution of the new image is much lower than the original one.
Below is an example of Image Pyramiding –
Advantages of Image pyramids:
- Lowering of resolution
- Getting various sizes of image
- Image Blending
- Edge detection
- Image Processing without OpenCV | Python
- Python | Image blurring using OpenCV
- Image Resizing using OpenCV | Python
- Reading an image in OpenCV using Python
- Image Translation using OpenCV | Python
- Image Registration using OpenCV | Python
- Cartooning an Image using OpenCV - Python
- OpenCV Python Program to blur an image
- Python | Detect corner of an image using OpenCV
- OpenCV Python Program to analyze an image using Histogram
- Python | OpenCV program to read and save an Image
- Find Circles and Ellipses in an Image using OpenCV | Python
- Python Program to detect the edges of an image using OpenCV | Sobel edge detection method
- Image Inpainting using OpenCV
- OpenCV | Saving an Image
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.