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Image scaling can be interpreted as a form of image resampling or image reconstruction from the view of the Nyquist sampling theorem.According to the theorem, downsampling to a smaller image from a higher-resolution original can only be carried out after applying a suitable 2D anti-aliasing filter to prevent aliasing artifacts.
One of the simpler ways of increasing the size, replacing every pixel with a number of pixels of the same color. The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest ...
A common scenario is to interpolate an image by using a bicubic interpolation which increases the image size by no more than 10% (110% of the original size) at a time until the desired size is reached. [1] Fred Miranda, a developer, popularized this method by creating and developing several Photoshop plug-ins that incorporate this technique. [2]
In image processing, bicubic interpolation is often chosen over bilinear or nearest-neighbor interpolation in image resampling, when speed is not an issue. In contrast to bilinear interpolation, which only takes 4 pixels (2×2) into account, bicubic interpolation considers 16 pixels (4×4).
When scaling up, Genuine Fractals exploits the self-similarity of an image to increase its size while preserving detail. In 1997, Genuine Fractals won a MacWorld Eddy. [ 5 ] It is also notable because Genuine Fractals was the first product developed on PC and ported to Mac to win an EDDY.
Add Text, crop, cut/copy selected area, paste-Into selected area, paste from print screen, resize/resample, rotate, flip vertically/horizontally, JPEG lossless transformations, color adjustments, change color depth, greyscale, red-eye reduction, sharpen, effects/filters, own and 8bf (Photoshop) plugins compatibility, edit IPTC info, move, copy ...
Like any resampling operation, changing image size and bit depth are lossy in all cases of downsampling, such as 30-bit to 24-bit or 24-bit to 8-bit palette-based images. While increasing bit depth is usually lossless, increasing image size can introduce aliasing or other undesired artifacts.
Sample-rate conversion, sampling-frequency conversion or resampling is the process of changing the sampling rate or sampling frequency of a discrete signal to obtain a new discrete representation of the underlying continuous signal. [1]
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