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The main purpose of pngcrush is to reduce the size of the PNG IDAT data stream by trying various combinations of compression methods and delta filters. It can also be used for various manipulations of PNG images, such as changing the bit depth , removing unwanted ancillary chunks , or adding certain chunks including gAMA, tRNS, iCCP, and ...
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.
The Quite OK Image Format (QOI) is a specification for lossless image compression of 24-bit (8 bits per color RGB) or 32-bit (8 bits per color with 8-bit alpha channel RGBA) color raster (bitmapped) images, invented by Dominic Szablewski and first announced on 24 November 2021.
On small images, GIF can achieve greater compression than PNG (see the section on filesize, below). On most images, except for the above case, a GIF file has a larger size than an indexed PNG image. PNG gives a much wider range of transparency options than GIF, including alpha channel transparency.
Sometimes, you find a drawing or similar image useful for a Wikipedia article, that was saved as a JPEG but should have been saved as a PNG.JPEG is good for images where the color changes fluidly throughout the image, like in a photograph, whereas PNG files are good for images with relatively few colors, such as a drawing of a flag, a chart, or a map; note that sometimes SVG is better.
Composite image showing JPG and PNG image 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 ...
Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...
Guetzli optimizes the quantization step of encoding to achieve compression efficiency. It constructs custom quantization tables for each file, decides on color subsampling, [4] and quantizes adjacent DCT coefficients to zero, balancing benefits in the run-length encoding of coefficients and preservation of perceived image fidelity.
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