This can preserve sharp details in pixel art, but also introduce jaggedness in previously smooth images. 'Nearest' in nearest-neighbor doesn't have to be the mathematical nearest. One common implementation is to always round towards zero. Rounding this way produces fewer artifacts and is faster to calculate. Bilinear and bicubic algorithms īilinear interpolation works by interpolating pixel color values, introducing a continuous transition into the output even where the original material has discrete transitions. Although this is desirable for continuous-tone images, this algorithm reduces contrast (sharp edges) in a way that may be undesirable for line art. Bicubic interpolation yields substantially better results, with an increase in computational cost. Sinc resampling in theory provides the best possible reconstruction for a perfectly bandlimited signal. In practice, the assumptions behind sinc resampling are not completely met by real-world digital images. Lanczos resampling, an approximation to the sinc method, yields better results. Bicubic interpolation can be regarded as a computationally efficient approximation to Lanczos resampling. One weakness of bilinear, bicubic and related algorithms is that they sample a specific number of pixels. 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.
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