Image derivative
An image derivative is a way to measure how fast an image is changing. It's like looking at a picture and seeing how much the colors or shapes are changing from one point to another.
Let's say you're looking at a picture of a smiley face. If you wanted to see how much the smiley face is changing from one point to another, you would use the image derivative. For example, you might look at how much the curves of the smile are changing or how much the colors of the eyes are changing.
To do this, you use something called a gradient, which is a fancy name for a set of numbers that tells you how much the colors or shapes are changing at each point in the image. You can think of it like a map where each point on the map has a number that tells you how steep the slope is at that point.
Image derivatives are used in lots of different areas, like computer vision and image processing, to help computers better understand and analyze images. So next time you see a cool image on your computer, remember that image derivatives helped make it possible!
Let's say you're looking at a picture of a smiley face. If you wanted to see how much the smiley face is changing from one point to another, you would use the image derivative. For example, you might look at how much the curves of the smile are changing or how much the colors of the eyes are changing.
To do this, you use something called a gradient, which is a fancy name for a set of numbers that tells you how much the colors or shapes are changing at each point in the image. You can think of it like a map where each point on the map has a number that tells you how steep the slope is at that point.
Image derivatives are used in lots of different areas, like computer vision and image processing, to help computers better understand and analyze images. So next time you see a cool image on your computer, remember that image derivatives helped make it possible!