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  2. Comparison gallery of image scaling algorithms - Wikipedia

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

    An adaptable technique which can deliver variable amounts of detail or smoothness. It aims to preserve the shape and coordinates of original details, without blurring those details into neighboring ones. It will avoid blending pixels which directly touch each other, and instead only blend pixels with their diagonal neighbors.

  3. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    An image scaled with nearest-neighbor scaling (left) and 2×SaI scaling (right) 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.

  4. ImageMagick - Wikipedia

    en.wikipedia.org/wiki/ImageMagick

    Transform: resize, rotate, crop, flip or trim an image. (Applies these without generation loss on JPEG files, where possible.) Transparency: render portions of an image invisible. Draw: add shapes or text to an image. Decorate: add a border or frame to an image. Special effects: blur, sharpen, threshold, or tint an image.

  5. 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.

  6. Wikipedia:Autosizing images - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Autosizing_images

    upright=0.8 – scales the image to approximately 80% of the user's default size (20% smaller) upright=1.2 – scales the image to approximately 120% of the user's default size (20% larger) left – shifts the image to the left margin; right – shifts the image to the right margin; center – shifts the image to center between left/right margins

  7. Difference of Gaussians - Wikipedia

    en.wikipedia.org/wiki/Difference_of_Gaussians

    In the simple case of grayscale images, the blurred images are obtained by convolving the original grayscale images with Gaussian kernels having differing width (standard deviations). Blurring an image using a Gaussian kernel suppresses only high-frequency spatial information. Subtracting one image from the other preserves spatial information ...