Archive for September, 2020

A look at VP1 and VP2

Saturday, September 26th, 2020

One of the issues with On2 VPx family is that they started it from VP3 while having four different TrueMotion codecs before that (it’s like the company was called Valve and not Duck at that time). But I wanted to look at some lossless audio codecs and there’s VocPack or VP for short which has versions 1 and 2. Bingo!

This is a very old lossless audio codec that appeared in 1993 along with Shorten and, as it turns out, originated the second approach to lossless audio compression. While Shorten was a simple format oriented on fast decoding and thus used fixed prediction (either LPC filter or even fixed prediction scheme) and Rice codes for residues (the same scheme used in FLAC and TAK), VocPack employed adaptive filter and arithmetic coding (the approach carried by LA, Monkey’s Audio, OptimFROG and such). And it was made for DOS and 8-bit audio! Well, version 2 added support for 16-bit but it seems to compress only high 8 bits of the sample anyway while transmitting low bits verbatim.

And it turned out to be my first real experience of using Ghidra with DOS executables. The main troubles were identifying library functions and dealing with pointers. Since it was compiled with Borland C++ 3.0 (who doesn’t remember it?) it was rather easy to decompile but library functions were not recognized (DOS executables don’t get much love these days…) but searching the disassembly for int 21h with Ralf Brown’s interrupts list at hand it was easy to identify calls for file operations (open/read/write/seek) and from those infer the stdio library functions using them and finally the code using all those getc()s. And of course segmented model makes decompiling fun, especially when decompiler can’t understand segment/offset variables being used separately. In result sometimes you recognize offset but you have to look at the data segment yourself to see what it refers to; even worse, for some local variables Ghidra seemed to assume wrong segment which resulted in variables in disassembly and decompiled output pointing to non-existent locations. Despite all of that it was rather easy to understand what unpacker for VP1 does. VP2 has only packer and no unpacker publicly available (feel free to trace the author and buy a copy from him that supports unpacking) plus it depends on those wrongly understood global variables more which prevented me from understanding how encoding a residue works there. In theory you should be able to set data segment manually but I don’t see a point on spending more than a couple of hours on REing the format.

It was a nice distraction though.

Lossless audio codecs were more advanced than I thought

Wednesday, September 23rd, 2020

As I’d mentioned in a previous post on lossless audio codecs, I wanted to look at some of them that are still not reverse engineered for documentation sake. And I did exactly that so now entries on LA, OptimFROG and RK Audio are not stubs any more but rather contain some information on how the codecs work.

And if you look at LA structure you see a lot of filters of various sizes and structure. Plus an adaptive weight used to select certain parameters. If you look at other lossless audio codecs with high compression and slow decoding like OptimFROG or Monkey's Audio you’ll see the same picture: several filters of different kinds and sizes layered over each other plus adaptive weights also used in residuals coding. Of course that reminded me of AV2 and more specifically about neural networks. And what do you know, Monkey's Audio actually calls its longer filters neural networks (hence the name NNFilter.h in the official SDK and you can spot it in the version history as well leaving no doubts that it’s exactly the neural networks it is named after).

Which leads me to the only possible conclusion: lossless audio codecs had been using neural networks for compression before it became mainstream and it gave them the best compression ratios in the class.

And if we apply all this knowledge to video coding then maybe in AV4 we’ll finally see some kind of convolution filters processing whole tiles and then the smaller blocks removing spatial redundance maybe with some compaction layers like many neural network designs have (or transforms for largest possible block size in H.265/AV1/AVS2) and expansion layers (well, what do you think motion interpolation actually does?) and using RNNs to code residues left from all the prediction.

Why Rust is not a mature programming language

Friday, September 18th, 2020

While I have nothing against Rust as such and keep writing my pet project in Rust, there are still some deficiencies I find preventing Rust from being a proper programming language. Here I’d like to present them and explain why I deem them as such even if not all of them have any impact on me.
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A Modest Proposal for AV2

Wednesday, September 16th, 2020

Occasionally I look at the experiments in AV1 repository that should be the base for AV2 (unless Baidu rolls out VP11 from its private repository to replace it entirely). A year ago they added intra modes predictor based on neural network and in August they added a neural network based loop filter experiment as well. So, to make AV2 both simpler to implement in hardware and improve its compression efficiency I propose to switch all possible coding tools to use misapplied statistics. This way it can also attract more people from the corresponding field to compensate the lack of video compression experts. Considering the amount of pixels (let alone the ways to encode them) in a modern video it is BigData™ indeed.

Anyway, here is what I propose specifically:

  • expand intra mode prediction neural networks to predict block subdivision mode and coding mode for each part (including transform selection);
  • replace plane intra prediction with a trained neural network to reconstruct block from neighbours;
  • switch motion vector prediction to use neural network for prediction from neighbouring blocks in current and reference frames (the schemes in modern video codecs become too convoluted anyway);
  • come to think about it, neural network can simply output some weights for mixing several references in one block;
  • maybe even make a leap and ditch all the transforms for reconstructing block from coefficients directly by the model as well.

In result we’ll have a rather simple codec with most blocks being neural networks doing specific tasks, an arithmetic coder to provide input values, some logic to connect those blocks together, and some leftover DSP routines but I’m not sure we’ll need them at this stage. This will also greatly simplify the encoder as well as it will be more of a producing fitting model weights instead of trying some limited encoding combinations. And it may also be the first true next generation video codec after H.261 paving the road to radically different video codecs.

From hardware implementation point of view this will be a win too, you just need some ROM and RAM for models plus a generic tensor accelerator (which become common these days) and no need to design those custom DSP blocks.

P.S. Of course it may initially be slow and work in a range of thousands FPS (frames per season) but I’m not going to use AV1 let alone AV2 so why should I care?

Revisiting lossless codecs…

Sunday, September 6th, 2020

I’ve decided to add a couple of lossless audio formats in a preparation for a long-term goal of having a NihAV-based player (the debug tool nihav-player that I currently have can’t really count for one especially considering how it does not play pure audio files and tends to deadlock in SDL audio thread).

So I’ve added nihav-llaudio crate with four most common formats for music I have, namely FLAC, Monkey’s Audio, TTA and WavPack. And I guess it’s time to revisit my opinion about various lossless audio formats now that I’ve (re)implemented support for some of them (I tried to summarise my views about them almost ten years ago). Let’s see what has changed since then:

  • I had a closer look at MPEG-4 ALS and it turned out to be rather interesting (and probably the only lossless audio codec with P-frames) but it also has somewhat insane options (like maximum prediction order of 1023 for LPC; or coding the whole file with just one I-frame and the rest being P-frames so no seeking is possible) and RLSLMS being broken (the reference decoder can’t decode the official reference samples) and it got no popularity at all;
  • TTA turned out to be very simple with a baffling rationale

    The sample count in a TTA1 frame is a multiple to 576 (sound buffer granule). Based on this, the “frame time” is defined as a constant 1.04489795918367346939. Thus, the sample count in a regular TTA1 frame determined as: regular TTA1 frame length = frame time * sample rate.

    I’m no mathematician so this does not form a coherent logical chain for me, I’d use something like “frame length in samples is sample rate rounded up to multiple of 576” instead of “sample rate multiplied by 256/245”. The main irritating point is that last frame contains less samples and you need to signal that it’s last frame (or merely check if you have enough bits left to decode a full frame after you decoded enough samples for the last frame). Oh, and TTA2 seems to be still in development.

  • And speaking about codecs in development, I don’t see new lossless audio codecs appearing after 2010. Either I got too old and don’t spot them or the interest has finally faded out. This might be because most people don’t buy music any more but rather rent it in some online store or use some streaming service. And those who still do probably use one of the old established codecs like FLAC.
  • And since I’ve mentioned it, my opinion on it has not changed and only got a bit more refined not that I have a decoder for it as well. Previously I thought FLAC is a simple format with a bad bitstream format that makes seeking hard. Now I know that FLAC is a simple format (fixed predictor or LPC up to order 32 and fixed Rice codes; the only thing that improves compression is splitting residues into partitions where optimal k for coding them can be selected) with horribly designed bitstream format.

    Normally lossless audio formats either store offsets for each frame or have an easily recognizable header, but FLAC is different. It’s obvious that the author was inspired by MPEG audio header design but those actually had frame sizes coded. Here in order to find where the frame ends you need either to decode it or calculate CRC for the data you read (and in the likely case of false positives also check that the data is followed by a valid header). One could argues that there’s often a seek table in FLAC file but for e.g. in luckynight.flac those entries are for multiples of ten seconds positions, making seeking to a more precise position a task of skipping frames (which is fun—see above).

  • WavPack is still the best designed format in my opinion though it would be nicer to have some initial header with various metadata instead of having it stored in the first block. Other than that still no objections.
  • And it turns out there’s lossless AAC compression that employs wavelet transform before LPC (it’s Chinese AAC though so who cares).

I remember reading somewhere (on Hydrogenaudio most likely) a brief story about development of several popular lossless audio codecs (even told by the author of one but I might be wrong). Essentially it’s not a NIH syndrome but very close: somebody develops a format, another guy finds a minor flaw the original developer refuses to address (my memory is hazy but I think there were such things mentioned as no plugin for some player or not supporting some tags) and develops another format. The amount of formats that came to existence because somebody wanted to create a format and could not keep it to himself is pretty large too.

But those days seem to be over and maybe I’ll reverse engineer some of those old codecs for documenting reasons as there’s very little risk that somebody would pick them up and make widespread now. Alternatively I can rant on newer formats sucking as well. Though why wait, let’s do it now:

  • AAC sucks because of the countless extensions and attempts to bundle various coding approaches under the same name (fun fact – “xHE-AAC” is actually pronounced as “MPEG-D you-suck”);
  • AV1 sucks because of the organisational structure and their decisions during (and after) the design stage;
  • AV2 is not here yet but it sucks for the same reason;
  • BlueTooth audio codecs suck in various ways (except SBC, it’s okay for the purpose), especially because of marketing them as high-definition and robust while in reality they rarely are;
  • Chinese codecs suck for being rip-offs of better-known codecs. It’s especially gross that one of them got standardised as IEEE 1857.2 AAC;
  • H.264 sucks because of countless extensions;
  • H.265 inherited some from H.264 and added the licensing situation on top of that;
  • MPEG-5 EVC sucks because it’s a Frankenstein monster constructed from bits from H.263-H.265;
  • Opus sucks for being designed for streaming case and used elsewhere;
  • Vector-based codecs suck because current tools are still not good enough to autovectorise complex shapes and recognize gradients.

Now back to doing nothing.