FLIF is a new lossless image file format that outperforms all other in image compression, transmission, editing and storing. For more visit flif.info.

1. A FRESH NEW LOSSLESS IMAGE FORMAT
Launch date: 3rd
October, 2015
Latest Release: 22nd
September, 2016

2. FLIF
Lossless FLIF
FLIF is a novel lossless image format which outperforms PNG, lossless
WebP, lossless BPG, lossless JPEG2000, and lossless JPEG XR in terms of
compression ratio.
Lossy FLIF
In developer’s opinion, at low qualities and for photographs,
dedicated lossy formats like WebP, JPEG or BPG still produce better
results. However, at very high-quality, we think lossy FLIF is a better
option.

3. WHY FLIF
 JPEG most popular right now. However JPEG-
 Is lossy
 trade off between the file size and the loss of visual quality
 no alpha channel support (doesn't support semi or fully transparent
pixels)
 PNG can be used to overcome disadvantages of JPEG. But-
 generated files are huge compared to lossy
 bandwidth consumed is large
Finding a way to save images without compromising on quality while having the
smallest possible file, is definitely important for the modern web and mobile world

4. FLIF is the winner
According to the compression experiments, FLIF(lossless) files are on
average:
14% smaller than lossless WebP,
22% smaller than lossless BPG,
33% smaller than brute-force crushed PNG files (using ZopfliPNG),
43% smaller than typical PNG files,
46% smaller than optimized Adam7-interlaced PNG files,
53% smaller than lossless JPEG 2000 compression,
74% smaller than lossless JPEG XR compression.

6. Works on any kind of image
FLIF does away with knowing what image format performs the best at any
given task.
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.
The conclusion? FLIF beats anything else in all categories.

7. Progressive and lossless
FLIF is lossless, but can still be used
in low-bandwidth situations, since
only the first part of a file is needed
for a reasonable preview of the
image.
Other lossless formats also support
progressive decoding (e.g. PNG
with Adam7 interlacing), but FLIF is
better at it. Here is a simple
demonstration video, which shows
an image as it is slowly being
downloaded:
Here’s a video example
(if the video does not play, you can
watch it here:
https://youtu.be/ByH7RMsMxBY)

8. Generation Loss
(For Lossy FLIF)
Generation loss is the loss of
quality between subsequent
copies or transcodes of data.
One advantage (of many) of
using a lossless format in a lossy
way (as opposed to using a
lossy format), is that
generation loss is not an issue.
Here’s a video example
(if the video does not play, you
can watch it here:
https://youtu.be/gJJachY651c
)

9. Technical Information
FLIF is based on MANIAC compression. MANIAC (Meta-Adaptive
Near-zero Integer Arithmetic Coding) is an algorithm for entropy
coding developed by Jon Sneyers and Pieter Wuille.
It is a variant of CABAC (context-adaptive binary arithmetic
coding), where instead of using a multi-dimensional array of quantized
local image information, the contexts are nodes of decision trees
which are dynamically learned at encode time. This means a much
more image-specific context model can be used, resulting in better
compression.

10. Tech Info contd (MNIAC)
This entropy encoding method is called “meta-
adaptive near-zero integer arithmetic coding”
(MANIAC). It is meta-adaptive since the context model
itself is adapted to the data
Proposed is a dynamic data structure as a context
model. It is essentially a decision tree (actually one tree
per channel), grown during encoding. Figure shows an
example MANIAC tree. Every internal (non-leaf) node has
a test condition: an inequality comparing one of the
context properties to a value. The child nodes
correspond to the two test branches. During encoding,
every leaf node contains one actual context (array of
chances) and two virtual contexts per property. At
decode time only the actual contexts are used.

11. Technical Information
Moreover, FLIF supports a form of progressive interlacing (essentially
a generalization/improvement of PNG's Adam7 interlacing) which
means that any prefix (e.g. partial download) of a compressed file
can be used as a reasonable lossy encoding of the entire image. In
contrast to other interlacing image formats (e.g. PNG or GIF),
interlaced FLIF encoding takes the interlacing into account in the pixel
estimation and in the MANIAC context model. As a result, the
overhead of interlacing is small, and in some cases (e.g. photographs)
interlaced FLIF files are even smaller than non-interlaced ones.

12. THANK YOU