Hello Tim,
thanks for your reply.
Hi,
I would be interested to hear the results of experiments comparing
Dirac Pro and J2K. I assume you will be comparing Intra Dirac,
i.e. Dirac Pro/SMPTE VC-2, with J2K?
yes, I'm playing with I-frames only atm and I want to see how much I
can get. When I played with j2k I got an impression that there's still
a lot of redundancy in hi-freq subbands which j2k just ignores. Then I
looked into Dirac model and - bingo! - I found something that looked
close to how I thought it should be...
I will probably try to merge j2k model into Dirac and try it. I will
let you know the results then...
As you say Dirac Pro's entropy modelling is quite different to
J2K. I doubt it yields a higher compression ratio - the objective
with Dirac Pro was to produce a simpler, less complex solution
rather than a higher compression ratio. However I would add that,
because Dirac Pro takes care to preserve the DC precision it can
have fewer visual artefacts than J2k (even if PSNR figures don't
show this). I say this because we have noticed that J2K, used for
video, can produce an annoying DC flicker even at quite low
compression ratios.
so if I correctly understand if I apply my j2k-based model to Dirac's
quantization output then I avoid this problem?
also it's a bit unexpected [for me] - I thought if you want to be
potentially faster then I'd expect you to split your data into the
small independent blocks for parallelization but not process it
hierarchically?
I did some (unpublished) experiments a few years ago comparing J2K
and Dirac Pro. With arithmetic coding enabled the compression
efficiency (for lossless coding) was almost identical for the two
codecs (some images were 1 or 2% better with one codec and the
other way round for other images). Interestingly when arithmetic
coding was disabled, so that entropy coding was only the fixed
variable length coding (interleaved exp-Golomb), the compression
efficiency of Dirac Pro only dropped by 20%. That is for lossless
coding arithmetic coding only appeared to give a compression gain
of 1.25. Given that arithmetic coding adds significantly to the
complexity of the codec some applications may prefer the option of
not using arithmetic coding in Dirac Pro for lower complexity at
the expense of slightly reduced compression.
In this direction I want to try to build a relatively big transition
table and use a q-coder. I hope that once the transition table is
tuned to specific [family of] PDFs it can give good results (i.e.
close to the real arithmetic coder). However I still didn't read what
theory says about the size of the table vs efficiency, so if it's
grows exponentially then it's possibly not going to work...
At the moment there are low delay profile hardware implementations
of Dirac Pro/SMPTE VC-2 available from Numedia Technology and from
Westwood Rock. Software implementations are available in the Open
Source Schroedinger software and from Entropy Wave.
thx for the info.
Regards,
Vladimir
Regards
Tim
Dr Tim Borer
Lead Engineer
BBC Research & Development
BBC Centre House
56 Wood Lane
London W12 7SB
At 20:46 30/10/2010, javasharp...@ukr.net wrote:
Hi,
I want to do some experiments with dirac and j2k and I have a
question. As I see dirac's entropy modelling is totally
different from that of j2k. It would be interesting to know
the rationale behind it. In particular if the j2k's entropy
modelling (together with the dirac's arithmetic encoder which
as I understans is more effective than j2k's quasi-arithmetic
encoder) what size decrease can be expected?
Thanks in advance,
Vladimir
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