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Components and libraries for Web applications and websites have been developed to optimize file requests and reduce page load times by shrinking the size of various files. JavaScript and Cascading Style Sheet (CSS) resources may be minified, preserving their behavior while considerably reducing their file size.
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 ...
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.
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. G4 typically achieves a 20:1 compression ratio. [citation needed] For an 8.5"×11" page scanned at 200 DPI, this equates to a reduction from ...
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:
WebP is a raster graphics file format developed by Google intended as a replacement for JPEG, PNG, and GIF file formats. It supports both lossy and lossless compression, [8] as well as animation and alpha transparency.
Using sub-blocks of 4×4 pixels gives a compression ratio of 4:1 assuming 8-bit integer values are used during transmission or storage. Larger blocks allow greater compression ("a" and "b" values spread over more pixels) however quality also reduces with the increase in block size due to the nature of the algorithm.
The primary difference between Block Truncation Coding and Color Cell Compression is that the former was designed to compress grayscale images and the latter was designed to compress color images. Also, Block Truncation Coding requires that the standard deviation of the colors of pixels in a block be computed in order to compress an image ...