[hugin-ptx] Re: Blending very large numbers of files

2010-12-17 Thread kfj


On 16 Dez., 18:49, Matthew Gates matthew...@gmail.com wrote:
 On 14 December 2010 22:48, kfj _...@yahoo.com wrote:

 Well, we have tarballs with the original plate jpegs split into small
 chunks.  That's how the data arrived to us after some processing by
 another   The tarballs contain sub-directories x1 x2 x4 etc.  x1 is
 the highest res.  Don't worry about the rest of the directories, they
 are just lower resolution version of the same data.

Okay, I had a first look at the tar ball you linked to. If I interpret
the data correctly, x64 is the lowest resolution and shows the
complete plate, and the other directories offer tiles at various
resolutions, with the highest resolution images contained in x1, where
there are 64*64 =4096 images. The data don't look to me as if they
were suffering from significant vignetting. The background of the
image has a slight reddish tint towards the center in the order of
magnitude of 10 (out of 256), but I don't think that would translate
into such a visible effect as can be seen on your sample stitch image.
So I'm a bit puzzled - is this maybe just one plate where the problem
we're trying to tackle isn't so visible? At any rate, to get an idea
of the overall quality of the data, it would be useful to have a set
of x64 plate images, covering an area of - or even better, the whole
sky. If you have the data uncompressed somewhere you could just lump
them together with a command like (including the appropriate metadata)

tar cvf x64.tar S*/x64/*.jpg S*/x64/*.hhh

The resulting tar file would be smaller than one of the pyramids,
since it would only contain 1792 images, one for each tar ball.
My reasoning here is that any vignette-like effect would be perfectly
visible on the x64 image, the higher-res tiles would not offer too
much extra information for the purpose at hand. The 1792 images at the
lowest resolution would offer an idea of the overall problem and need
for processing and, therefore, be more useful than an arbitrary
pyramid with all resolutions - I suppose the x64 image is nothing but
a compressed composite of the higher-res tiles anyway.

The tiles come with a cornucopia of metadata, most of which exceed my
admittedly narrow astronomic horizon - what I seem to have gleaned,
though, is that the projection is gnomonic and localization of the
individual images should be easy straight from the metadata. What I
need for a trial stitch in hugin (from which we might be able to
derive the vignetting data) is translation of the astronomical
nomenclature in the hhh files into hugin's system. Hugin uses a notion
of roll, pitch and yaw. I suspect roll will be zero for the images,
pitch would refer to the center of the image and be in degrees from
the equator and yaw to the center of the image in degrees from any
reference point on the equator you care for, maybe you could point me
to which of the metadata to touch for the purpose and how to translate
them, if necessary. I suspect the relevant data are in the 'Hour
Angle' and 'Zenith distance' data fields in the hhh file, hour angle
could be translated straight into yaw, and Zenith distance would be
pitch + 90 degrees? I could then extract them from the hhh files.
Alternatively, put small files with the images containing roll, pitch
and yaw in degrees - then I wouldn't have to do the extraction
myself ;-)

 The x64 directories in the .tgz files might be useful here, as they
 are full-plate at low res.  We could maybe extract these, experiment
 with blending and even stitch them together into a panorama to check
 it.  1792 300x300 tiles isn't so bad.

 I can do the extraction of this data on the server and create a single
 archive file which should be a manageable size.

Sounds very good; I fully agree, hope to see the data soon!

with regards
Kay

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[hugin-ptx] Re: Blending very large numbers of files

2010-12-17 Thread kfj


On 17 Dez., 08:09, Pablo d'Angelo pablo.dang...@web.de wrote:
 If you want to try the hugin vignetting correction, one needs to know
 corresponding pixels between the overlapping plates. There are two
 possibilities:

 1. Add support for the input image (plate) format to hugin, and write a
 script that creates a PTO file from the metadata in the plate files.
 Then the standard workfow could be used (on the x64 images). The
 corresponding parameters could then be used for radiometric correction
 of the individal plates. If we add the toast projection, to panotools,
 it would be possible to directly output toast, otherwise its possible to
 produce corrected plate images.

I think that's a good path for now; the pto should be easy to make -
I've had a look at the attached metadata and it does look like it's
all there (wish all the other incoming images were only half as well
documented - these astronomers sure are precise...)

 Looking athttp://porpoisehead.net/images/dss_blend_needed.jpg
 I'm a bit sceptical how well it might work with hugins vignetting
 correction though.

so am I

 Do you know if the position of the plate in the
 telescopes focal plane is available in the metadata? Do you have a
 document describing the metadata?

I my notion of astronomy isn't wrong, I suppose it's one plate at a
time right bang in the middle where the focal point of the mirror is.
Center of image = optical axis, which should be normal to the image
plane. Then leave the plate there for an hour with the telescope
slowly rotating to make up for the earth's rotation, then next plate -
as long as the night lasts and there are no clouds. Matthew, please
correct me if I'm wrong.

 For a first experiment, a smaller subset of the mosaic would be
 sufficient, maybe a 5x5 grid. For this test, the alignment could be done
 in hugin to avoid the steps I have mentioned before. The full data will
 be a real challange, even when using the tiny images.

I disagree. At the lowest resolution, so at x64, the total amounts to
a measly 161 Megapixels, transfer volume much less since the JPGs are
quite cruelly compressed [this surprises me - I'm almost certain the
true source data would not be JPG and the pyramids at hand are already
a few steps down the processing pipeline...] The real work is writing
the script from the metadata. Also it seems to me that the problems
are more pronounced in some areas than other. Best to have the full
x64 set.

 The full mosaic would be much simpler, if we had a reference image
 that covers the whole mosaic. It only needs to contain the background
 brightness, not all the stars etc. This would make the vignetting
 correction much simpler and probably yield a nicer result.

We would have that if we stitched together the x64 tiles, and since
they are so precisely located, this stitch should come out really
well.

with regards
Kay

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[hugin-ptx] Re: have you heard about TOAST projection?

2010-12-17 Thread kfj


On 16 Dez., 15:50, Seb Perez-D sbprzd+...@gmail.com wrote:
 On Thu, Dec 16, 2010 at 15:48, Sebastien Perez-Duarte

 sebastien.perez-dua...@m4x.org wrote:
  A much better projection is the Peirce Quincuncial. It is also square,
  but is almost everywhere conformal.

 Sorry, I forgot the Wikipedia link!

 http://en.wikipedia.org/wiki/Peirce_quincuncial_projection

Hey, I really like this projection! You're right, it has more
aesthetic appeal than TOAST.

Kay

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Re: [hugin-ptx] Re: Blending very large numbers of files

2010-12-17 Thread Matthew Gates
On 17 December 2010 12:57, kfj _...@yahoo.com wrote:
 The tiles come with a cornucopia of metadata, most of which exceed my
 admittedly narrow astronomic horizon - what I seem to have gleaned,
 though, is that the projection is gnomonic and localization of the
 individual images should be easy straight from the metadata. What I
 need for a trial stitch in hugin (from which we might be able to
 derive the vignetting data) is translation of the astronomical
 nomenclature in the hhh files into hugin's system. Hugin uses a notion
 of roll, pitch and yaw. I suspect roll will be zero for the images,
 pitch would refer to the center of the image and be in degrees from
 the equator and yaw to the center of the image in degrees from any
 reference point on the equator you care for, maybe you could point me
 to which of the metadata to touch for the purpose and how to translate
 them, if necessary. I suspect the relevant data are in the 'Hour
 Angle' and 'Zenith distance' data fields in the hhh file, hour angle
 could be translated straight into yaw, and Zenith distance would be
 pitch + 90 degrees? I could then extract them from the hhh files.
 Alternatively, put small files with the images containing roll, pitch
 and yaw in degrees - then I wouldn't have to do the extraction
 myself ;-)

I hope Fabien will join in the conversation here.  He's been dealing
with the processing of these images into the toast projection and so
is much more familiar with this stuff than me.

 The x64 directories in the .tgz files might be useful here, as they
 are full-plate at low res.  We could maybe extract these, experiment
 with blending and even stitch them together into a panorama to check
 it.  1792 300x300 tiles isn't so bad.

 I can do the extraction of this data on the server and create a single
 archive file which should be a manageable size.

 Sounds very good; I fully agree, hope to see the data soon!

Here's a tarball with the x64 images and their associated meta-data files:

  http://porpoisehead.net/misc/dss_low.tar.gz (~11 meg)

I'm assuming the N??? ones are for the Northern hemisphere and the
S??? files are for the Southern hemisphere, but this should become
apparent from the metadata analysis.

Matthew

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[hugin-ptx] why is vertical line detection so hard?

2010-12-17 Thread Jeffrey Martin
ok, i will also take my thoughts from this thread 
https://groups.google.com/forum/#!topic/hugin-ptx/27hdrRBxVYY and expand on 
it in a new thread.
*
Why can't any (known) software do automatic vertical line detection (and 
thus levelling) of images?
*
I know it's a hard problem. But I suspect it is something that has 1) been 
solved already in some some proprietary systems that we don't know about and 
2) not important enough to have been solved in academia or other places, 
where we would have heard about it.

I'm interested to hear anybody's thoughts on this matter.

cheers!
Jeffrey

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[hugin-ptx] Re: why is vertical line detection so hard?

2010-12-17 Thread kfj


On 17 Dez., 15:52, Jeffrey Martin 360cit...@gmail.com wrote:

 Why can't any (known) software do automatic vertical line detection (and
 thus levelling) of images?

So you're quite specific about _vertical_ line detection. Line
detection per se isn't really a problem, and I think there's even
software in the hugin bundle that uses line detection (doesn't the
lens calibration tool do so?). The trouble is just - how would you
know that any given line in any image is vertical and not some other
orientation? So you either need to make preliminary assumptions (i.e.
images are roughly upright, lines within a certain angle range from
'up' are considered) - or, again, you need user input.
The current mechanism for levelling uses a statistical approach, but
doesn't really look at the images. You could look at it as some sort
of user input, though: the user would have tried to hold the camera
upright, and the statistics makes the best of it. Maybe if the current
mechanism was applied first and then detected lines were looked for
which were 'near assumed vertical' an automatic detection could be
attempted.

with regards
Kay

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Re: [hugin-ptx] Re: why is vertical line detection so hard?

2010-12-17 Thread Jan Martin
Hi Kay,

I would like to have automatic leveling too.

Assuming that someone is at least trying to get it right, all those
assumptions are perfectly valid.

Jan


On Fri, Dec 17, 2010 at 4:45 PM, kfj _...@yahoo.com wrote:



 On 17 Dez., 15:52, Jeffrey Martin 360cit...@gmail.com wrote:

  Why can't any (known) software do automatic vertical line detection (and
  thus levelling) of images?

 So you're quite specific about _vertical_ line detection. Line
 detection per se isn't really a problem, and I think there's even
 software in the hugin bundle that uses line detection (doesn't the
 lens calibration tool do so?). The trouble is just - how would you
 know that any given line in any image is vertical and not some other
 orientation? So you either need to make preliminary assumptions (i.e.
 images are roughly upright, lines within a certain angle range from
 'up' are considered) - or, again, you need user input.
 The current mechanism for levelling uses a statistical approach, but
 doesn't really look at the images. You could look at it as some sort
 of user input, though: the user would have tried to hold the camera
 upright, and the statistics makes the best of it. Maybe if the current
 mechanism was applied first and then detected lines were looked for
 which were 'near assumed vertical' an automatic detection could be
 attempted.

 with regards
 Kay

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[hugin-ptx] Re: Blending very large numbers of files

2010-12-17 Thread Fabien
On Dec 17, 3:02 pm, Matthew Gates matthew...@gmail.com wrote:
 On 17 December 2010 12:57, kfj _...@yahoo.com wrote:



  The tiles come with a cornucopia of metadata, most of which exceed my
  admittedly narrow astronomic horizon - what I seem to have gleaned,
  though, is that the projection is gnomonic and localization of the
  individual images should be easy straight from the metadata. What I
  need for a trial stitch in hugin (from which we might be able to
  derive the vignetting data) is translation of the astronomical
  nomenclature in the hhh files into hugin's system. Hugin uses a notion
  of roll, pitch and yaw. I suspect roll will be zero for the images,
  pitch would refer to the center of the image and be in degrees from
  the equator and yaw to the center of the image in degrees from any
  reference point on the equator you care for, maybe you could point me
  to which of the metadata to touch for the purpose and how to translate
  them, if necessary. I suspect the relevant data are in the 'Hour
  Angle' and 'Zenith distance' data fields in the hhh file, hour angle
  could be translated straight into yaw, and Zenith distance would be
  pitch + 90 degrees? I could then extract them from the hhh files.
  Alternatively, put small files with the images containing roll, pitch
  and yaw in degrees - then I wouldn't have to do the extraction
  myself ;-)

 I hope Fabien will join in the conversation here.  He's been dealing
 with the processing of these images into the toast projection and so
 is much more familiar with this stuff than me.

  The x64 directories in the .tgz files might be useful here, as they
  are full-plate at low res.  We could maybe extract these, experiment
  with blending and even stitch them together into a panorama to check
  it.  1792 300x300 tiles isn't so bad.

  I can do the extraction of this data on the server and create a single
  archive file which should be a manageable size.

  Sounds very good; I fully agree, hope to see the data soon!

Hi,
I'm Fabien from Stellarium brought here by Matthew.

 Here's a tarball with the x64 images and their associated meta-data files:

  http://porpoisehead.net/misc/dss_low.tar.gz(~11 meg)

 I'm assuming the N??? ones are for the Northern hemisphere and the
 S??? files are for the Southern hemisphere, but this should become
 apparent from the metadata analysis.

Yes N stands for North, S for South.
So I am not not completely sure what we need as input: I think for
what we need we can make the assumption that the plate projection is
gnomonic. In this case I can extact the lon/lat positions of the 4
corners of each plate. Then what do we need to do with that? Can
the .pto be generated from just that?
Fabien

 Matthew

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[hugin-ptx] Re: Blending very large numbers of files

2010-12-17 Thread kfj


On 17 Dez., 15:02, Matthew Gates matthew...@gmail.com wrote:

 Here's a tarball with the x64 images and their associated meta-data files:

  http://porpoisehead.net/misc/dss_low.tar.gz(~11 meg)


Thank you. I have already had a go at the data, but no conclusive
result. I'd like to discuss my assumptions about the metadata, while
hugin is having a hard time swallowing a pto file with almost 900
images ;-)

obvious:
- The metadata are organized in 80-character blocks
- The heading 8 characters, followed by a '=' sign, contain the field
name
- next are 30 characters are value, followed by an optional comment

what I extracted:
- I have taken the field CRVAL1 (commented: Rectascension of the
reference pixel)
- And the field CRVAL2 (Declination of same) as yaw and pitch, roll
zero
- I have assumed the hfov to be 6.6266 degrees approximately, but I'm
unsure here:
  it's half-guessed, combined from the fields:
  PLTSCALE=  67.2000 /Detector: Plate Scale arcsec per
mm
  PLTSIZEX=355.0 /Detector: Plate X dimension
mm
  and this may well be wrong. please help me with the field of view -
I'm not sure if the whole plate dimension goes into the 300X300 tile
or just some part of it.
- there are the fields CRPIX1 and CRPIX2, each valued 61.0, denoting
the
  'X Refernce and Y Refernce Pixel'. Does this mean that the
rectascension and
  declination do not refer to the tile center? I need help with that,
as well.

I batch-extracted the metadata with a python script which wrote out
the pto file, the pto goes like

p w2000 h1000 f2
o nN002_00_00_x64.jpg w300 h300 f0 v6.62 r0.0 y15.701600
p83.455875
o nN003_00_00_x64.jpg w300 h300 f0 v6.62 r0.0 y53.398000
p83.397969
...

I did a trial stitch with a subset of about 100 images and it came out
looking plausible, but with stars it's of course hard to tell if the
overlap is right. Currently I asked hugin to do a sample stitch with
the whole northern data and my assumed positions and fovs, this should
take a long while if it succeeds at all. I'll keep you posted, it
would be nice if you could help with the metadata.

with regards
Kay

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[hugin-ptx] Re: Blending very large numbers of files

2010-12-17 Thread kfj


On 17 Dez., 17:51, Fabien fabien.cher...@googlemail.com wrote:

 Hi,
 I'm Fabien from Stellarium brought here by Matthew.

Hi Fabien. Sorry, our posts crossed, I was busy writing up mine while
yours came in

 Yes N stands for North, S for South.
 So I am not not completely sure what we need as input: I think for
 what we need we can make the assumption that the plate projection is
 gnomonic. In this case I can extact the lon/lat positions of the 4
 corners of each plate. Then what do we need to do with that? Can
 the .pto be generated from just that?

As you can see from my previous post, I've already made some
assumptions here. For the pto to work, our reference needs to be to
the center of the tile and we need the horizontal field of view. I'll
have to dig into the reference if hugin can take gnomonic source data
- if not, it shouldnt'be too hard to transform to rectilinear, though
every transformation degrades the data. For my trial I've assumed
rectilinear which shouldn't be too far off for an initial test (or
isn't it even the same, come to think of it?). The precise field of
view of the actual 300X300 tile is absolutely crucial to make the
overlap correct. the other issue concerning the precise location of
the refernce point is as crucial - if the reference is to another
point than the center, the RA/Dec values have to be recalculated for
the image center, which shouldn't be too hard. I'd need to know where
(0,0) is, though - bottom left with y up?
Apart from that I see no problems - if hugin can't swallow the lot in
one go, we can just make like two dozen strips and blend them in a
second step - my hugin job is already done warping and the blender is
half done loading the warped tiles.
Once these initial technicalities are dealt with we can proceed to
deal with the real issue, which is the detection and possible removal
of assumed vignetting artefacts.

with regards
Kay

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