Image scaling

It has been suggested that Pixel art scaling algorithms and Resampling be merged into this article or section. (Discuss)

In computer graphics, image scaling is the process of resizing a digital image. Scaling is a non-trivial process that involves a trade-off between efficiency, smoothness and sharpness. As the size of an image is increased, so the pixels which comprise the image become increasingly visible, making the image appear "soft". Conversely, reducing an image will tend to enhance its smoothness and apparent sharpness.

Apart from fitting a smaller display area, image size is most commonly decreased (or subsampled or downsampled) in order to produce thumbnails. Enlarging an image (upsampling or interpolating) is generally less common. The main reason for this is that in "zooming" an image, it is not possible to discover any more information in the image than already exists, and image quality inevitably suffers. However, there are several methods of increasing the number of pixels that an image contains, which evens out the appearance of the original pixels.

Scaling methods

An image size can be changed in several ways. Consider doubling the size of the following image:

The easiest way of doubling its size is nearest-neighbor interpolation, replacing every pixel with four pixels of the same color:

The resulting image is larger than the original, and preserves all the original detail, but has undesirable jagginess. The diagonal lines of the W, for example, now show the characteristic "stairway" shape.

Other scaling methods are better at preserving smooth contours in the image. For example, bilinear interpolation produces the following result:

Linear (or bilinear, in two dimensions) interpolation is typically better than the nearest-neighbor system for changing the size of an image, but causes some undesirable softening of details and can still be somewhat jagged. Better scaling methods include bicubic interpolation:

For magnifying computer graphics with low resolution and/or few colors (usually from 2 to 256 colors) the best results will be achieved by hq2x or similar scaling algorithms. These produce sharp edges and maintain high level of detail:

For scaling photos (and raster images with lots of colors) see also anti-aliasing algorithms called supersampling.

See also

• Pixel art scaling algorithms
• Bicubic interpolation
• Bilinear interpolation
• Lanczos resampling
• Spline interpolation
• Seam carving
• Supersampling

External links

• B/W and color scaling
• Interpolation by Vincent Bockaert
• General Scaling - Leptonica
• FreeImage Display Demo

This computer graphics-related article is a stub. You can help Wikipedia by expanding it. v • d • e