What is Interpolation?
Updated Saturday, November 06, 1999
by Randy Glass - Copyright 1999 by the Feather River Canyon News - All rights reserved.These images may not be stored, reproduced, or distributed in any way without the expressed written permission of the Editor of the Feather River Canyon News.
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So you have an image that is about 640x480 and you would like to print it at 8x10 to frame and give to Grandma. The problem is that you know that if you just print it that big that the picture will look like a mosaic tile close-up. All those little pixels that are just about invisible at around 4x5 will start to show like crazy at 8x10. What to do... what to do?|
It is time to interpolate! Interpolation is a way to add pixels that aren't really there to make an image print properly at sizes larger then normal. Let's look at an example to get an idea of what this is all about:
Lets say you have an image that is 1000x500 pixels in size, and your printer prints at 250dpi, and you print the image at its 'natural' size (not shrunk or expanded). The print size will be 4 inches by 2 inches. But what if you want everything to remain the same as above, and you want to print that image at 8 inches by 4 inches? It doesn't take a math major to see that something has to give. Either the print resolution has to drop to 125dpi or you need more pixels. Well, that's what interpolation does. It fills in the missing pixels (for the above example you would need four times as many pixels- twice as wide and twice as tall; 2x2=4). That's a lot of information to be made up. Why bother? Sure, you can just make the image four times larger and print it, but the results will be less than satisfying. The image will look quite pixelated- blocky.
There are a number of different interpolation algorithms, and depending on how 'smart' the interpolation method is in your printing application will greatly affect image quality. Interpolation problems show themselves in different ways. Sometimes you will notice a 'blockiness.' Small areas of low resolution that were quite dark in the original image (like a shadow on a rock) will turn to larger black rectangles. Another place to look is fine lines that run at angles such as high contrast edges between a building and the sky, power lines, hand rails, and such. These turn into 'zippers' or 'ziggy-zaggies' when poorly interpolated.
Take a look at these example images. They will help explain interpolation a bit:
As you can see, there is always a trade off- No free lunches. Interpolated images can become soft. The algorithm can add so many pixels in such a heavy-handed manner that the image gains a soft focus look. When you have a choice, use a higher resolution image and don't try to print it too large. When that can be done (such as when you are printing a bunch of high resolution images at 4x5") it is best to not use any interpolation. But when you want to print an 8x10 from a 1280x960 image, a good interpolation algorithm can be indispensable for producing useable output.
How do you choose an interpolation method that is best for you? Some applications don't give you a choice. When you do have a choice, experiment. Variables such as what printer, paper, ink, and printing application you use along with the image itself will dictate what method to use.