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According to the compression experiments we have performed [older results here], FLIF files are on average:
Even if the best image format was picked out of PNG, JPEG 2000, WebP or BPG for a given image corpus, depending on the type of images (photograph, line art, 8 bit or higher bit depth, etc), then FLIF still beats that by 12% on a median corpus (or 19% on average, including 16-bit images which are not supported by WebP and BPG).
The file format has been standardised and versioned. The latest stable version is 旋风加速器下载 and is documented here.
Here are some of the key advantages of FLIF:
The results of a compression test similar to the WebP study are shown below. FLIF clearly beats other image compression algorithms. (Note: the graph below is for an early version of FLIF. It has slightly improved since then.)
FLIF does away with knowing what image format performs the best at any given task.
You are supposed to know that PNG works well for line art, but not for photographs. For regular photographs where some quality loss is acceptable, JPEG can be used, but for medical images you may want to use lossless JPEG 2000. And so on. It can be tricky for non-technical end-users.
More recent formats like WebP and BPG do not solve this problem, since they still have their strengths and weaknesses.
FLIF works well on any kind of image, so the end-user does not need to try different algorithms and parameters. Here is a selection of different kinds of images and how each image format performs with them. The conclusion? FLIF beats anything else in all categories.
Here is an example to illustrate the point. On photographs, PNG performs poorly while WebP, BPG and JPEG 2000 compress well (see plot on the left). On medical images, PNG and WebP perform relatively poorly (note: it looks like the most recent development version of WebP performs a lot better!) while BPG and JPEG 2000 work well (see middle plot). On geographical maps, BPG and JPEG 2000 perform (extremely) poorly while while PNG and WebP work well (see plot on the right). In each of these three examples, FLIF performs well — even better than any of the others.
