Thanks Tomxe for that info.
Found a github page with test JPEG XL images at
https://github.com/alistair7/jxl-community.github.io/tree/main (file is 348 Mb)
Also found:
JPEG XL Image Loader for imlib2
This is a loader for imlib2 that
adds support for reading and writing JPEG XL files.
Windows/Linux releases here:
https://github.com/libjxl/libjxl/releases/from the page
https://github.com/alistair7/libjxlTo encode a source image to JPEG XL with default settings:
cjxl input.png output.jxl
To decode a JPEG XL file run:
djxl input.jxl output.png
That Github page says:
When possible, cjxl/djxl are able to read/write the following image formats: OpenEXR (.exr), GIF (.gif), JPEG (.jpg/.jpeg), NetPBM (.pam/.pgm/.ppm), Portable FloatMap (.pfm), PGX Test Format (.pgx), Portable Network Graphics (.png), Animated PNG (.png/.apng), and JPEG XL itself (.jxl).
Also found:
Jpegli: an improved JPEG encoder and decoder implementationThe development of jpegli, the improved JPEG encoder and decoder, will continue at https://github.com/google/jpegliThis repository contains a JPEG encoder and decoder implementation that is API and ABI compatible with libjpeg62.
https://github.com/google/jpegliInfo from the page:
https://opensource.googleblog.com/2024/04/introducing-jpegli-new-jpeg-coding-library.htmlJpegli is a new JPEG coding library that is designed to be faster, more efficient, and more visually pleasing than traditional JPEG. It uses a number of new techniques to achieve these goals, including:
It provides both a fully interoperable encoder and decoder complying with the original JPEG standard and its most conventional 8-bit formalism, and API/ABI compatibility with libjpeg-turbo and MozJPEG.
High quality results. When images are compressed or decompressed through Jpegli, more precise and psychovisually effective computations are performed and images will look clearer and have fewer observable artifacts.
Fast. While improving on image quality/compression density ratio, Jpegli's coding speed is comparable to traditional approaches, such as libjpeg-turbo and MozJPEG. This means that web developers can effortlessly integrate Jpegli into their existing workflows without sacrificing coding speed performance or memory use.
10+ bits. Jpegli can be encoded with 10+ bits per component. Traditional JPEG coding solutions offer only 8 bit per component dynamics causing visible banding artifacts in slow gradients. Jpegli's 10+ bits coding happens in the original 8-bit formalism and the resulting images are fully interoperable with 8-bit viewers. 10+ bit dynamics are available as an API extension and application code changes are needed to benefit from it.
More dense: Jpegli compresses images more efficiently than traditional JPEG codecs, which can save bandwidth and storage space, and speed up web pages.
Looks like they are always making changes and updating.