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An image size can be changed in several ways. Consider resizing a 160x160 pixel photo to the following 40x40 pixel thumbnail and then scaling the thumbnail to a 160x160 pixel image. Also consider doubling the size of the following image containing text.
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.
This is an accepted version of this page This is the latest accepted revision, reviewed on 31 December 2024. Lossy compression method for reducing the size of digital images For other uses, see JPEG (disambiguation). "JPG" and "Jpg" redirect here. For other uses, see JPG (disambiguation). JPEG A photo of a European wildcat with the compression rate, and associated losses, decreasing from left ...
Typically, compressions using lossless operation mode can achieve around 2:1 compression ratio for color images. [5] This mode is quite popular in the medical imaging field, and defined as an option in DNG standard, but otherwise it is not very widely used because of complexity of doing arithmetics on 10, 12, or 14bpp values on typical embedded 32-bit processor and a little resulting gain in ...
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.
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.
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