pngquant is a command-line utility for converting 24/32-bit PNG images to paletted (8-bit) PNGs.
The conversion reduces file sizes significantly (often as much as 70%) and preserves full alpha transparency. Generated images are compatible with all modern web browsers, and have better fallback in IE6 than 24-bit PNGs.
Current version is 1.7.2 (changelog, feed, old versions).
sudo dpkg -i pngquant_1.7.1-1_*.deb)dpkg-source -x pngquant_1.7.1-1.dsc; cd pngquant-1.7.1; debuild)pngquant and other tools by Kornel Lesiński.pngquant).Written in C99. Available under a BSD-like license. The project is hosted on GitHub.
git clone git://github.com/pornel/improved-pngquant.gitpngquant 256 *.png
… | pngquant 16 | …
To further reduce file size, you may want to consider optipng or ImageOptim.
See pngquant -h for full list of options.
-ext new.pngSet custom extension for output filename. By default -or8.png or -fs8.png is used.
-speed NSpeed/quality trade-off from 1 (brute-force) to 10 (fastest). The default is 3. Speed 10 has 5% lower quality, but is 8 times faster than the default.
-iebugWorkaround for IE6, which only displays fully opaque pixels. pngquant will make almost-opaque pixels fully opaque and will avoid creating new transparent colors.
-versionPrint version information to stdout.
-Read image from stdin and send result to stdout.
--Stops processing of arguments. This allows use of file names that start with -. If you're using pngquant in a script, it's advisable to put this before file names:
pngquant $OPTIONS -- "$FILE"pngquant uses modified version of Median Cut quantization algorithm and additional techniques to mitigate deficiencies of Median Cut.
Instead of splitting boxes with largest volume or number of colors, boxes are selected to minimize variance from their median value.
Histogram is built with addition of a basic perception model, which gives less weight to noisy areas of the image.
To improve color further, histogram is adjusted in a process similar to gradient descent (Median Cut is repeated many times with more weight on poorly represented colors).
Finally, colors are corrected using Voronoi iteration, which guarantees locally optimal palette.
pngquant works in premultiplied alpha color space to give less weight to transparent colors.
When remapping, error diffusion is applied only to areas where several neighboring pixels quantize to the same value, and which are not edges. This avoids adding noise to areas which have high visual quality without dithering.
pngnq — image quantizer using NeuQuant algorithm