Increasing Image Resolution-Make Your Photos Bigger With Minimal Loss in Quality

From: http://graphicssoft.about.com/cs/resolution/a/increasingres.htm

One of the most commonly asked questions in relation to graphics software is how to increase the size of an image without getting blurring and jagged edges. New users are often surprised when they resize an image and find that the quality is severely degraded. Experienced users are all too familiar with the problem. The reason for the degradation is because bitmapped, or raster, image types are limited by their pixel resolution. When you attempt to resize these types of images, your software either has to increase the size of each individual pixel - resulting in a jagged image - or it has to "guess" at the best way to add pixels to the image to make it larger.

 

Not long ago, there weren't many options for increasing resolution other than using your editing software's built-in resampling methods. Today, we are faced with more possibilities than ever. Of course, it's always best to capture the resolution you need right from the beginning. If you have the option to rescan an image at a higher resolution, by all means, you should do that before resorting to software solutions. And if you have the money to put into a camera capable of higher resolutions, you might find that money is better spent than if you were to put it into a software solution. Having said that, there are often times when you may have no other choice than to resort to software. When that time comes, here's the information you should know.

 

Resizing vs. Resampling

Most software only has one command for both resizing and resampling. Resizing an image involves changing the print dimensions without changing the total pixel dimensions. As the resolution is increased, the print size becomes smaller, and vice versa. When you increase resolution without changing pixel dimensions, there is no loss in quality, but you must sacrifice print size. Resizing an image using resampling, however, involves changing the pixel dimensions and will always introduce a loss in quality. That's because resampling uses a process called interpolation for increasing the size of an image. The interpolation process estimates the values of the pixels the software needs to create based on the existing pixels in the image. Resampling via interpolation results in serious blurring of the resized image, especially in areas where there are sharp lines and distinct changes in color.

• About Image Size & Resolution

 

Common Interpolation Methods

Photo editing software generally offers a few different interpolation methods for calculating new pixels when an image us upsampled. Here are descriptions of the three methods available in Photoshop. If you don't use Photoshop, your software probably offers similar options although they may use slightly different terminology.

Bicubic is the slowest but produces the best estimation of new pixel values.

Bilinear is faster than bicubic, but does a poorer job. Both bicubic and bilinear interpolation result in a blurred image, especially when upsampling.

Nearest Neighbor doesn't use interpolation. It simply takes the value of the neighboring pixels and adds new pixels without averaging them. This is when you get the jaggies or stair-step effect.

Note that there are more than just these three methods of interpolation and even using the same method in different software may produce different results. In my experience, I have found that Photoshop offers the best bicubic interpolation of any other software that I have compared.

• Photoshop's Image Size Dialog Box

 

Continue to part two to learn about other interpolation methods: stair interpolation, LizardTech Genuine Fractals, and more.