libjpeg

libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, AVX2, Neon, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, Arm, and PowerPC systems, as well as progressive JPEG compression on x86, x86-64, and Arm systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines. In many cases, the performance of libjpeg-turbo rivals that of proprietary high-speed JPEG codecs.

libjpeg-turbo implements both the traditional libjpeg API as well as the less powerful but more straightforward TurboJPEG API. libjpeg-turbo also features colorspace extensions that allow it to compress from/decompress to 32-bit and big-endian pixel buffers (RGBX, XBGR, etc.), as well as a full-featured Java interface.

libjpeg-turbo was originally based on libjpeg/SIMD, an MMX-accelerated derivative of libjpeg v6b developed by Miyasaka Masaru. The TigerVNC and VirtualGL projects made numerous enhancements to the codec in 2009, and in early 2010, libjpeg-turbo spun off into an independent project, with the goal of making high-speed JPEG compression/decompression technology available to a broader range of users and developers.

Project Page (Code repository, issue/feature trackers)

Mailing Lists (Google Groups)

Official Binaries and Source Tarballs ()

If you have benefited from this product, then please consider making a donation to ensure that we can continue to provide this enterprise-quality, high-performance software free of charge and in a vendor-neutral manner. Every dollar donated goes toward the development of libjpeg-turbo. Alternately, if you have any improvements in mind for the product, please consider funding the labor necessary to implement them.

*** Projects in need of funding ***

2019-02-04: libjpeg-turbo Becomes Official ISO/ITU-T Reference Implementation

2016-05-02: libjpeg-turbo Named SourceForge Project of the Month, May 2016