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Old 6th August 2007, 15:51   #1  |  Link
Terka
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DV dropout

Which filter is suitable for eliminating dropouts in presenting in DV source .
What I mean as dropout: in DV sometimes a part of the picture is missing or damaged.
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Old 6th August 2007, 19:42   #2  |  Link
cwk
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BadFrames creates a blend of the previous and next frame and uses this to replace the current one. To use this plugin, you will need to know which frames require replacing beforehand. The plugin asks for specific frame numbers.

If you don't know the damaged frames before, or if there are too many to specify, you can use conditionalfilter (internal to avisynth) to replace frames based on certain conditions.

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Old 7th August 2007, 00:58   #3  |  Link
IanB
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For best results this really needs to be done as part of the decoding process when the DV syntax errors are first detected.

Perhaps you can make a request in the DV forum for an enhancement to Cedocide to output some form of colour key mask information in the decoded images. i.e YUV=$000000 or $ffffff invalid pixel values indicating these areas need repair.

Once you have the information any of the many techniques for masking in replacment data can be used. It may be as simple as copy the equivalent pixels from the previous frame to as complicated as a full motion vector recontructions from several adjacent frames.
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Old 7th August 2007, 01:16   #4  |  Link
Mug Funky
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here's the one i use. success varies depending on the length of the dropout and the complexity of the motion.

Code:
function morph (clip c, int in, int "out", int "blksize")
{

	Function fill_loop(string s, int stop, int count)
	{
		return (stop == 0) ? s : string("tofill.mvflowinter(fill_vb,fill_vf,time=" + string(100*(count - stop)/float(count))) + ",thscd1=255,thscd2=255).selectevery(tofill.framecount(),0)," + fill_loop(s,stop-1,count)
	}

out=default(out, 0)
blksize=default(blksize,16)

d=c.trim(in,out)# in-1?

numframes=d.framecount-2
tofill=d.selectevery(c.framecount(),0,c.framecount()-1)

fill_vf=tofill.mvanalyse(truemotion=true,blksize=blksize,pel=2,isb=false,overlap=blksize/2)
fill_vb=tofill.mvanalyse(truemotion=true,blksize=blksize,pel=2,isb=true,overlap=blksize/2)
filled=eval("interleave(" + fill_loop("" ,d.framecount()-1,d.framecount()-1) + "tofill.selectevery(tofill.framecount(),tofill.framecount())).assumefps(c.framerate())")
c.trim(0,in-1)++filled++c.trim(out+1,0)
}
usage:

find the dropout visually (you really should watch what you encode anyway, though i never did - there's other people for that ), then:

morph(inframe, outframe)

where inframe and outframe are the first good frames adjacent to the glitch.

you'll probably need to photoshop the output of this and re-insert the stills with imagesource, too.

this is quite effective when there's not too many glitches, but it can get tedious when you've got a crap master - in which case a re-shoot is in order
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Old 7th August 2007, 09:47   #5  |  Link
Terka
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thank you!
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Old 14th October 2011, 02:12   #6  |  Link
Mounir
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Excellent script, just what i needed,
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Old 14th October 2011, 06:45   #7  |  Link
Ghitulescu
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Quote:
Originally Posted by Terka View Post
Which filter is suitable for eliminating dropouts in presenting in DV source .
What I mean as dropout: in DV sometimes a part of the picture is missing or damaged.
Have you tried first to clean your player?
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