The Effects of Interpolation in Digital Photography

How pixel size and interpolation are related

A digital camera on a tripod.

Kiyoshi Hijiki / Getty Images 

Enlarging a digital photo commonly entails interpolation—a process that increases the size of pixels within an image.

Some digital cameras—most point-and-shoot cameras and phones—use interpolation to produce digital zoom. This allows you to focus on subjects beyond the maximum range allowed by the camera's lens. Image manipulation programs such as Adobe Photoshop also use interpolation in post-production editing.

Generally, there are four types of interpolation: nearest-neighbor, bilinear, bicubic, and fractal. Knowing a bit about each can help you get the most from your photography.

Digital zoom is software-based and employs some form of interpolation. In contrast, optical zoom relies on an actual, physical lens to magnify a distant image. Optical zoom produces clearer, higher-quality photos than does digital zoom. If you're using one of these cameras, moving closer to the subject will give you a better shot than using the digital zoom.

Increasing an image's size is generally inadvisable. Interpolation adds information to the original image, which can introduce blurriness, artifacts, pixelation, and other issues that can degrade the image's quality.

Nearest-Neighbor Interpolation

Nearest-neighbor interpolation is most commonly used in-camera to review your shots and to enlarge them so you can see details. It simply makes the pixels bigger, and the color of a new pixel is the same as the nearest original pixel. It's not suitable for enlarging images for print because it can produce jaggies—also known as pixelation.

Example of pixelation

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. Images enlarged this way can become blurry.

Bicubic Interpolation

Bicubic interpolation is the most sophisticated of the bunch. It relies on 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 can produce print-quality images. Bicubic interpolation has two variants to help you fine-tune your image: "smoother" and "sharper."

Although this 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 specific professional-level software to run. Professional printers often use fractal interpolation.