The Effects of Interpolation in Digital Photography

How pixel size and interpolation are related

A digital camera on a tripod.

Kiyoshi Hijiki / Getty Images 

When you increase the size of a digital image, some form of interpolation takes place and it can significantly affect the quality of the photograph. It is important for photographers to understand what interpolation is and how to improve its results.

What Is Interpolation?

Interpolation is a term used to describe a method to increase the size of pixels within an image. It is commonly used to increase the overall size of an image.

Increasing an image's size is generally not advised because the computer needs to use interpolation to add information that was not originally there. The effects of this can vary based on the type of interpolation used but, in general, it is not good.

As the computer tries to interpret what new information needs to be added, the image can become blurry or have small points of color or tone that seem out of place.

Some digital cameras (most point and shoot cameras and phones) use interpolation to create the 'digital zoom.' This means that the camera can zoom in beyond the maximum range allowed by the camera's lens (called optical zoom). If using one of these cameras, it is often best for you to move closer to the subject rather than using the digital zoom.

Interpolation is most often used in camera imaging software and this is where the photographer really needs to understand the different types of interpolation.

Nearest Neighbor Interpolation

Nearest neighbor interpolation is most commonly used in-camera when reviewing and enlarging images to view details. It simply makes the pixels bigger, and the color of a new pixel is the same as the nearest original pixel.

Disadvantage: It is not suitable for enlarging images for print as it can produce jaggies.

Bilinear Interpolation

Bilinear interpolation takes the information from an original pixel, and four of the pixels that touch it, to decide on the color of a new pixel. It produces fairly smooth results, but it reduces the quality significantly.

Disadvantage: Images can become blurry.

Bicubic Interpolation

Bicubic interpolation is the most sophisticated of the bunch, as it takes information from the original pixel and 16 surrounding pixels to create the color of a new pixel.

Bicubic interpolation is far more advanced than the other two methods, and it is capable of producing print-quality images. Bicubic interpolation also offers the two variants of "Smoother" and "Sharper" for finely tuned results.

Disadvantage: Though it is one of the best options, too big of a jump in size can still reduce image quality.

Fractal Interpolation

Mainly used for very large prints, fractal interpolation samples from even more pixels than bicubic interpolation. It produces sharper edges and less blurring but requires very specific software to run it. Professional printers often use fractal interpolation.

Disadvantage: Most computer software does not have this option.