Motion-compensating YUV4MPEG-frame denoiser
see also :
mpeg2enc - yuvdenoise - yuvmedianfilter
[-v verbosity] [-p parallelism]
[-r motion-search_radius] [-R
reference_frames] [-B] [-I
interlacing_type] < /dev/stdin >
add an example, a script, a trick and tips
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can be used to remove noise from images in a YUV4MPEG2
stream. This is useful for cleaning old sources to increase
video quality, and to reduce the bitrate needed to encode
your video (e.g. for VCD and SVCD creation).
accepts the following options:
-v [0..2] verbosity
0 = none, 1 = normal (per-frame
pixel-detection totals), 2=debug.
Controls the level of
parallelism. Since intensity and color are denoised
separately by design, it’s very easy to do each in
parallel on a multiple-processor machine. The default value
is 1; that reads and writes video frames in parallel with
denoising. A value of 2 causes intensity and color to be
denoised in parallel. A value of 3 does both types of
concurrency. A value of 0 turns off all concurrency.
-r [4..] search
The search radius, i.e. the
maximum distance that a pixel can move and still be found by
motion-detection. The default is 16. There are no particular
restrictions on the search radius, e.g. it doesn’t
have to be an even multiple of 4.
-R [4..] color
The search radius to use for
color. Default is whatever the main search-radius was set
to. Note that this value ends up getting scaled by the
relative size of intensity & color planes in your
The largest difference between
two pixels that’s accepted for the two pixels to be
considered equal. The default is 3, which is good for
medium-noise material like analog cable TV. (This value will
have to be changed to whatever is appropriate for your
YUV4MPEG2 stream in order to avoid undesirable results. See
the instructions below.)
Error tolerance for color
The default is whatever the
main error-tolerance was set to.
Error tolerance for zero-motion pass
The error-tolerance used on
pixels that haven’t moved. Usually equal to the main
error-tolerance or one less than that. Default is 2.
Error tolerance for color’s zero-motion pass
The default is whatever the
main zero-motion error-tolerance was set to.
The maximum number of
pixel-group matches (within the search radius) to consider.
If more are found, only the closest matches are kept.
Default is 15.
The minimum size of the
flood-filled region generated from a match. Matches smaller
than this are thrown away. Specified in terms of
pixel-groups. Default is 3.
The number of reference frames
to keep. Pixel values are averaged over this many frames
before they’re written to standard output; this also
implies that output is delayed by this many frames. Default
Black-and-white mode. Denoise only the intensity plane,
and set the color plane to all white.
Set interlacing type. Default
is taken from the YUV4MPEG2 stream. 0 means not interlaced,
1 means top-field interlaced, 2 means bottom-field
interlaced. This is useful when the signal is more naturally
of some other interlacing type than its current
representation (e.g. if the original was shot on film and
then later it was transferred to interlaced video, it will
denoise better if treated as film, i.e. non-interlaced).
If you have questions, remarks, problems or you just want to
contact the developers, the main mailing list for the MJPEG-tools
For more info, see our website at
how it works
It maintains a list of the last several frames, called reference
frames. Each reference frame is composed of reference pixels.
Every time a pixel in one frame is proven to be a moved instance
of a pixel in another frame, the reference-pixel incorporates its
value, and produces an average value for all instances of the
pixel. The oldest reference frame, therefore, gets a pretty good
idea of the real value of every pixel, but of course output is
delayed by the number of reference frames.
The search is not actually done one pixel at a time; it’s
done in terms of pixel groups. An entire pixel-group has to match
for any match to be found, but all possible pixel-groups are
tested (i.e. all possible overlapping combinations are checked).
Using pixel-groups helps to establish a minimum standard for what
may be considered a match, in order to avoid finding lots of
really small (and really useless) matches. Presently, intensity
pixel-groups are 4x2 (i.e. 4 across and 2 down), and color
pixel-groups are 2x2.
It compares every pixel-group in the current frame with all
pixel-groups in the previous frame, within a given search-radius,
and sorts them based on how close the match was, keeping the top
contenders. It then flood-fills each found pixel-group in turn,
to determine the full size of the match. The first match found to
be big enough is applied to the image. The number of contenders
to consider, and the minimum size of a match, can be specified on
the command line.
At the end of the frame, any new-frame pixels not resolved yet
are considered to be new information, and a new reference-pixel
is generated for each one.
A "zero-motion pass" happens each frame, before motion-detection,
in an attempt to resolve most of the frame cheaply. Its
error-tolerance can be set separately.
typical usage and tips
Keep in mind that all of this advice was gained through
experience. (Just because one writes a tool doesn’t mean
one understands how it should be used, for the same reason that
car designers aren’t necessarily professional drivers.)
The error-threshold must be determined for every individual
YUV4MPEG2 stream. If the threshold is set too low, it’ll
leave noise in the video, and the denoiser will run a lot slower
than it has to. If it’s set too high, the denoiser will
start to remove detail: the video will get blurrier, you may see
topographical-like bands in the relatively flat areas of the
video, and small parts of the video that should be moving will be
stuck in place. It may also run a little slower. Additionally,
just because the video came to you from a clean source (digital
cable TV, LaserDisc, etc.) doesn’t mean the video itself is
clean; y4mdenoise is capable of picking up on noise in the
original recording as well as sampling error from the
video-capture device. You will have to generate small clips of
representative parts of your video, denoise them with various
error thresholds, and see what looks the best. As you gain
experience with the tool, you may know what error threshold
generally works with various types of sources, but you’ll
still want to double-check your assumptions.
Flat, shiny surfaces, like gloss-painted walls, or the polished
wood floor of an indoor gymnasium, seem to require a lower error
threshold than other types of video.
Here is the author’s experience:
-t 1 : Digital cable TV, most LaserDiscs, DV camcorder video
-t 2 : VHS camcorder video, commercially-produced videotapes
-t 3 : Analog cable TV, VHS videotape (at the 2-hour speed)
-t 4 : VHS videotape (at the 6-hour speed)
Interlaced video that was made from non-interlaced video (e.g. a
videotape or LaserDisc of a film) must be denoised as
non-interlaced. Otherwise the result tends to be grainy.
y4mdenoise only removes temporal noise, i.e. noise that
occurs over time. And it tends to do such a good job of this,
that the spatial noise (i.e. noise that occurs in nearby areas of
the same frame) tends to become very distinct. Therefore, always
pipe the output of y4mdenoise through a spatial filter
such as y4mspatialfilter or yuvmedianfilter.
When producing very low bitrate video (e.g. VCD-compatible video
less than 900 kbps), denoise at the output frame size, e.g.
don’t denoise at DVD frame size then downscale to VCD size.
That will denoise as well as condition the video for the
motion-detection part of mpeg2enc. Not doing this will
produce video where the less complex scenes will look really
good, but high-motion scenes will blur significantly.
JPEG compression of your video frames, even 100% compression,
seems to be inaccurate enough to affect MPEG encoding. Therefore,
if you’re using motion-JPEG files as your intermediary
video format, you may want to use the denoiser in your
MPEG-encoding pipeline, i.e. after lav2yuv and before
mpeg2enc. If you’re generating multiple resolutions
of the same video, e.g. DVD and VCD, experience shows that
it’s acceptable to run y4mdenoise before
yuv2lav, but you should still use the spatial-filter (e.g.
y4mspatialfilter, yuvmedianfilter) in the
MPEG-encoding pipeline, to try to smooth away JPEG encoding
mpeg2enc , yuvdenoise ,
The bulk of the
y4mdenoise code, and this manual page, was written by
Steven Boswell <ulatec[:at:]users.sourceforge[:dot:]net>.