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  2. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    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-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.

  3. Image compression - Wikipedia

    en.wikipedia.org/wiki/Image_compression

    Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.

  4. Seam carving - Wikipedia

    en.wikipedia.org/wiki/Seam_carving

    Original image to be made narrower Scaling is undesirable because the castle is distorted. Cropping is undesirable because part of the castle is removed. Seam carving. Seam carving (or liquid rescaling) is an algorithm for content-aware image resizing, developed by Shai Avidan, of Mitsubishi Electric Research Laboratories (MERL), and Ariel Shamir, of the Interdisciplinary Center and MERL.

  5. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    Left side of the image is from a low-quality JPEG image, showing lossy artefacts; the right side is from a PNG image. In information technology , lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content.

  6. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    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.

  7. Group 4 compression - Wikipedia

    en.wikipedia.org/wiki/Group_4_compression

    Both G3-2D and G4 add a two-dimensional feature to achieve greater compression by taking advantage of vertical symmetry. A worst-case image would be an alternating pattern of single-pixel black and white dots offset by one pixel on even/odd lines. G4 compression would actually increase the file size on this type of image.

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  9. Quantization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Quantization_(image...

    This technique is commonly used for simplifying images, reducing storage requirements, and facilitating processing operations. In grayscale quantization, an image with N intensity levels is converted into an image with a reduced number of levels, typically L levels, where L<N. The process involves mapping each pixel's original intensity value ...

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