Digital Subband Video 2 - Open Source Wavelet Codec

[LMP88959]

Hello Doom9, I've released the second iteration of my video codec.

https://github.com/LMP88959/Digital-Subband-Video-2

DSV1 wasn't giving me the performance I wanted so I continued work on it and created DSV2.

DSV2 is to DSV1 what MPEG-4 Part 2 was to MPEG-2. A similar 'generational leap' in terms of efficiency.


Comparison video (you can see a couple more comparisons in the README of the repository):
minih264:
https://github.com/user-attachments/...7-ba6b66a98d59
DSV2:
https://github.com/user-attachments/...f-74cb59e05333

It is totally free for you to use however you'd like.


Description taken from GitHub README:

DSV2 Features

• compression using multiresolution subband analysis instead of DCT
• also known as a wavelet transform
• up to quarter-pixel motion compensation
• 4:1:1, 4:2:0, 4:2:2 (+ UYVY) and 4:4:4 chroma subsampling formats
• adaptive quantization
• in-loop filtering
• intra and inter frames with variable length closed GOP
• no bidirectional prediction (also known as B-frames). Only forward prediction with previous picture as reference
• only form of entropy coding is interleaved exponential-golomb coding for simplicity

Improvements and New Features since DSV1

• in-loop filtering after motion compensation
• more adaptive quantization potential
• skip blocks for temporal stability
• new subband filters + support for adaptive subband filtering
• better motion compensation through Expanded Prediction Range Mode (EPRM)
• quarter pixel compensation
• psychovisual optimizations in the codec and encoder design

[benwaggoner]

Can you give an architectural overview of how you're handling inter prediction in wavelets? Wavelets were always pretty good for intraframe compression, but weren't able to match block-based motion compensation efficiency.

I've long thought that this was due to the better symmetry between inter and intra in block-based coding, which minimized cumulative loss from using visibly compressed blocks to predict from.

Being able to do more wavelet-like interprediction always seemed like the holy grail here, but I at least never had a good idea how that would work in practice.

[LMP88959]

Hi Ben,

DSV2 does block-based motion compensation as well using the 'traditional' techniques of subpel motion and in-loop 'deblocking' filtering.
The wavelets are only used for intra frame and inter (residual) frame compression.

Did I understand your question correctly?

[benwaggoner]

Originally Posted by LMP88959

Hi Ben,

DSV2 does block-based motion compensation as well using the 'traditional' techniques of subpel motion and in-loop 'deblocking' filtering.
The wavelets are only used for intra frame and inter (residual) frame compression.

Did I understand your question correctly?

Yes, perfectly.

Is the deblocking to handle artifacts introduced by the pixel-based motion estimation?

Do you find mixing wavelet-based and pixel-based tools is a challenge for efficient motion prediction? My sense is this has been a big reason that wavelet codecs haven't been competitive for interframe encoding to date.

Many years ago I idly imagined a way to use 3D wavelets to extend into the temporal dimension to get around this. But my approach was so obviously awful I didn't get very far with it .

The Daala experimental approach of keeping everything in the frequency domain for prediction and only rasterizing for display seemed like it might be more promising for wavelets than it proved to be for a block-based transform.

Wavelets are a fascinating topic! And get used in things like digital projectors in movie theaters and the beloved Cineform codec. The intrinsic spatially scalable properties seem like they'd be well suited to a lot of internet applications if temporal prediction bitrate scaled with the subbands...

[LMP88959]

Originally Posted by benwaggoner

Yes, perfectly.

Is the deblocking to handle artifacts introduced by the pixel-based motion estimation?

Do you find mixing wavelet-based and pixel-based tools is a challenge for efficient motion prediction? My sense is this has been a big reason that wavelet codecs haven't been competitive for interframe encoding to date.

Yes the deblocking filter is to handle sharp discontinuities introduced by the motion compensation.

From what I've learned, a full-frame wavelet codec like DSV2 is unable to realistically test the entropy of potential predictions since it would be very unreasonable to subtract the prediction for a block, transform+quantize the whole frame, and then estimate the number of bits (or some other metric) that prediction would result in.

DCTs and wavelets are essentially opposites of each other. A DCT coefficient represents a pattern over a certain 2D area whereas a wavelet coefficient represents a 'feature' at a certain point in an area. As a result, what traditional DCT codecs are good at coding may be nightmarish for a wavelet and vice versa.
I say all this to bring attention to the fact that these differences must be taken into consideration when doing ME and mode decision.

Some might call this opinion a stretch, however, I believe H.264's concept of intra prediction is as effective as it is because it essentially combined wavelets and the DCT. Of course, wavelets weren't being directly used, but the removal of a gradient in a block is similar to a wavelet decomposition where you'd have one coefficient in a lower level subband which represents a gradient in the horizontal/vertical/diagonal direction over a certain part of an image.

Originally Posted by benwaggoner

Many years ago I idly imagined a way to use 3D wavelets to extend into the temporal dimension to get around this. But my approach was so obviously awful I didn't get very far with it .

Interestingly enough, I began the DSV project last year in an attempt to make a decent wavelet based video codec after seeing how virtually every codec was either using the DCT or (in the old days) VQ.
When I started the project I originally tried that 3D wavelet idea.
It had a few big issues:
1. Very slow.
2. High memory requirement (relatively)
3. Ineffective at temporal prediction.

Temporally, a Haar wavelet would be the best because it does not introduce much ringing at all but at the same time it's essentially the same as simple frame differencing. Any other wavelet would result in weird ghosting and blurring in the temporal domain.

Originally Posted by benwaggoner

The Daala experimental approach of keeping everything in the frequency domain for prediction and only rasterizing for display seemed like it might be more promising for wavelets than it proved to be for a block-based transform.

Wavelets are a fascinating topic! And get used in things like digital projectors in movie theaters and the beloved Cineform codec. The intrinsic spatially scalable properties seem like they'd be well suited to a lot of internet applications if temporal prediction bitrate scaled with the subbands...

The idea of doing motion estimation using the wavelet decompositions of both the source and reference frames instead of the pixels themselves sounds interesting, I wonder how well it would work in practice...

Thank you for the great comments and questions!

[benwaggoner]

Thanks for your feedback! I love hearing about novel codec designs. I hadn't considered wavelets and DCT as inverses of each other. I'll need to spend some shower time ruminating on that.

I had tangential involvement with JPEG XR when I was at Microsoft. It had alternating DCT and wavelet spatial enhancement layers, which I thought was a fascinating approach. A fundamentally ineffective one, though. Some smart people spent a long time trying to make an encoder that would meaningfully outperform JPEG perceptually, which in theory was easy, but in practice wasn't accomplished. If that had worked, doing block-based motion estimation on the DCT layer and only using the wavelets for spatial enhancement could have been an interesting possibility.

Alas, so many good ideas just don't work in the end. The Daala development notes are a fascinating journey through trying lots of novel, clever ideas and having most of them prove impractical.

[LMP88959]

Of course, and thank you for your curiosity!
With the little experience I have, I can naively say there is a good amount of potential in mixing wavelets and DCTs in a codec.
And I agree, the Daala development pages are very interesting and document the various novel techniques quite well. They also often describe the fundamental problems they're trying to solve with each technique which helps newbies like myself understand what a codec needs to do.

[LMP88959]

Since last time I posted, I've made a few improvements to DSV2.

- Motion estimation uses RMSE instead of SAD
- Better mode decision
- Added a new psychovisual metric. Found in hme.c, block_has_vis_edge(). (may be interesting to a curious reader or other encoder developer out there)
- Replaced the high freq filter with something interesting and relatively unexplored (as far as I know) since ~1990, an asymmetric subband filter.

In my opinion, the most fascinating addition by far is the asymmetric subband filtering.
Asymmetric in this context means the encoding is considerably slower than decoding. It is lossy, but such asymmetry is a rare thing in transform based coding where the inverse transform is typically just as complex as the forward transform.


Check out the pull request here:
https://github.com/LMP88959/Digital-...Video-2/pull/9

Quote from the pull request:

Adding a new subband filter (which I'm calling ASF93 for reasons explained below) for increased intra frame decoding performance.
...
This new filter is only applied to level 1 (to create the highest frequency subbands). It is asymmetrical and does not allow for perfect reconstruction.

Subband filtering consists of a FIR filter bank that splits up a signal into different subbands. Wavelets and the Haar transform are all special cases of subband filters.
In subband filtering, the forward transform is called 'analysis' and the inverse transform is called 'synthesis.'

With ASF93, the analysis filters are 9-tap filters. The FIR coefficients were tuned to my personal psychovisual tastes (slightly emphasized low pass features, noisy/ringy but localized high pass features). The synthesis FIR filter coefficients are the standard 3-tap filters used elsewhere in DSV2. The name ASF93 stands for "asymmetric subband filter with 9-tap analysis and 3-tap synthesis."

Reference for the idea:
Subband image coding with three-tap pyramids by
E H Adelson and E P Simoncelli (1990)

Strangely, I haven't been able to find anything else regarding this concept of asymmetrical subband filtering besides this paper, which is unfortunate. I believe there is some untapped potential here.
I hope this update to DSV2 will help push this effort forward as well as provide a modern use-case.