Why yet another image format?
Current image formats have integrated compression, making it complicated to read the image data. One is forced to use complex libraries like libpng, libjpeg, libjpeg-turbo, giflib and others, read the documentation and write a lot of boilerplate in order to get started.
Farbfeld leaves this behind and is designed to be as simple as possible, leaving the task of compression to external tools. The simple design, which was the primary objective, implicitly leads to the very good compression characteristics, as it often happens when you go with the UNIX philosophy. Reading farbfeld images doesn’t require any special libraries. The tools are just a toolbox to make it easy to convert between common image formats and farbfeld.
How does it work?
In Farbfeld, pattern resolution is not done while converting, but while compressing the image. For example, farbfeld always stores the alpha-channel, even if the image doesn’t have alpha-variation. This may sound like a big waste at first, but as soon as you compress an image of this kind, the compression-algorithm (e.g. bz2) recognizes the pattern that every 48 bits the 16 bits store the same information. And the compression-algorithms get better and better at this.
Same applies to the idea of having 16 bits per channel. It sounds excessive, but if you for instance only have a greyscale image, the R, G and B channels will store the same value, which is recognized by the compression algorithm easily.
This effectively leads to filesizes you’d normally only reach with paletted images, and in some cases bz2 even beats png’s compression, for instance when you’re dealing with grayscale data, line drawings, decals and even photographs.
Why use 16-Bits-per-channel all the time? Isn’t this a total waste?
Not when you take compression into account. To make this clearer, assume a paletted image with 5 colors and no transparency. So the data is only a set of regular chunks (color1, …, color5) in a certain order. Compression algorithms have been designed to recognize those chunks and can even look at how these chunks interact.
Local tests have shown that farbfeld easily beats paletted PNG-images. Try for yourself and look at the bzipped results! There is no need for special grayscale, palette, RGB, 1-, 2-, 4-, 8-, 16-Bit subformats. Just use 16-Bit RGBA all the time and let compression take care of the rest.
Which compression should I use?
bzip2 is recommended, which is widely available (anybody has it) and gives good results. As time will move forward and new algorithms hit the market, this recommendation might be rethought.
What about NetPBM?
NetPBM is considered to be the most simple format around, however, there’s much room for improvement. In fact, it doesn’t help that the format is subdivided into Portable BitMaps, Portable GrayMaps and Portable PixMaps. It’s not helpful when a manpage can’t give a simple overview of a format in a few sentences.
NetPBM’s big vice is that it has originally been developed to be hand-written and passed around as plain text. A binary format exists, but still handling optional comments in the header, base 10 ASCII width and height values, arbitrary whitespace inside the data and out-of-band image size and color depth is too painful for the sane user.
Judging from the usage of the format considering how long it’s been around, it’s no surprise it never really took off. Additionally, functionality like alpha channels and 16-Bit color depth can only be achieved via extensions. Due to it being a textual format it also lacks the desired compression characteristics.
The question you have to ask yourself is: Can I read in a format without consulting the manpages? If your answer is yes, then the format is simple enough. In this regard, NetPBM can be considered to be a failed format.