Upsampling is like making a small picture bigger. Imagine you draw a little picture on a small piece of paper. If you want to make the picture bigger so you can see more details, you can use a photocopier to make a bigger version of that small picture.
In computer terms, when we have a digital image, we can use a program to make it bigger by adding more pixels to the image. There are different ways to do this, but the most common approach is called upsampling. It's like taking a small image and increasing its size by adding more pixels to fill in the gaps.
For example, imagine you have a small image that is only 10 pixels wide and 10 pixels tall. If you want to make it twice as big, you need to add more pixels to it. You can use upsampling to create a new image that is 20 pixels wide and 20 pixels tall, with each pixel in the new image representing 4 pixels in the original image.
Upsampling can be useful in many situations. It can help improve the quality of digital images, especially when you need to print them or display them on a larger screen. It can also help in computer vision and machine learning applications, where you need to analyze images and extract information from them.
However, it's important to note that upsampling can also have some drawbacks. When you increase the size of an image by adding pixels, you run the risk of losing some of the original details and introducing artifacts or noise. That's why it's important to use upsampling techniques carefully and consider the trade-offs between image quality and resolution.