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Tourist attractions in Birbhum district In computer graphics and digital imaging, image scaling refers to the resizing of a digital image.

In video technology, the magnification of digital material is known as upscaling or resolution enhancement.

When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric transformations, with no loss of image quality.

When scaling a raster graphics image, a new image with a higher or lower number of pixels must be generated.

In the case of decreasing the pixel number (scaling down) this usually results in a visible quality loss.

From the standpoint of digital signal processing, the scaling of raster graphics is a two-dimensional example of sample-rate conversion, the conversion of a discrete signal from a sampling rate (in this case the local sampling rate) to another.

Image scaling can be interpreted as a form of image resampling or image reconstruction from the view of the Nyquist sampling theorem.

A more sophisticated approach to upscaling treats the problem as an inverse problem, solving the question of generating a plausible image, which, when scaled down, would look like the input image.

One of the simpler ways of increasing image size is nearest-neighbor interpolation, replacing every pixel with the nearest pixel in the output; for upscaling this means multiple pixels of the same color will be present.

When down scaling below a certain threshold, such as more than twice for all bi-sampling algorithms, the algorithms will sample non-adjacent pixels, which results in both losing data, and causes rough results.

Another solution to the downscale problem of bi-sampling scaling are mipmaps.

When downscaling the nearest larger mipmap is used as the origin, to ensure no scaling below the useful threshold of bilinear scaling is used.

Edge-directed interpolation algorithms aim to preserve edges in the image after scaling, unlike other algorithms, which can introduce staircase artifacts.