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(If you respond to this, please CC me, because I am *not* on FITSBITS.)
Here are a few cents of mine; I will ask Dustin Lang to follow up as well. I warn you that I am writing this *without* having read the documents, but I figure if I wait until I read the documents, I will never get my comments in in time. ----- We have been using SIP at http://astrometry.net/ for a few years now, and have working C and Python code that manipulates, creates, writes, and reads SIP. Overall, we like SIP, for the main reason: (0) SIP is very clear and simple, to read, implement, adjust, and analyze. We adopted SIP over TNX at the time for two reasons: (1) SIP was in image coordinates, TNX was in sky coordinates (at the time, this may have changed), and we expect *most* (not all) fixed distortions to be fixed in camera and not sky coordinates. (2) SIP made use of the usual FITS keywords, and did not require a string keyword manipulator to extract distortion coefficients, as TNX did at the start (don't know if it does still). My main problems or issues with SIP are as follows: (3) The inverse transformation is just a separate transformation and there is no restriction that the inverse *actually be* the inverse or any approximation to it. Indeed, it can't be an exact inverse. However, computers are smart and fast, so the inverse *could* have been encoded as the Newton's method inverse of the forward, and only one transformation would be stored in the header at all! I consider this an issue for a number of reasons: (3.1) is it wrong to invert the transformation by iterating the forward transformation? If so, how do we prevent that? (3.2) there are many ways to approximate the reverse transformation with a polynomial, and different investigators will make different choices (least squares on the calibration stars? least squares on arbitrary control points? use errors how?). This is not standardized, I suspect, in the standard. If it *were* standardized, would we force SIP readers to check that? (4) The restriction to 9th order may not seem restrictive, but if you know your camera has repeatable radial distortions, and you have millions of images, then you can easily fit radial terms beyond 9th order. Up to 9, these can be encoded as a SIP with many terms set to exactly zero. After 9, no dice. (5) The standard does not prevent an investigator from inputting a distortion map that is multi-valued, folded, and non-invertible, in forward or in reverse. In fact, once you get to high enough order, it is very hard to write a SIP header that does *not* have these problems somewhere in the "focal plane". There is one over-arching problem with all of these standards, which perhaps deserves addressing: (6) If you read the definitional WCS papers, the authors were clearly thinking of WCS to describe the mapping of a processed, output map. They were not thinking of using WCS to describe obtained, natural images. They were imagining that the investigator deals with all the natural images in some idiosyncratic way, produces a distortion-free map, and specifies the properties of that map using the WCS convention. That is *not* the way WCS is used in most applications, and leads to some of the compromises encountered in TNX and SIP. Finally, one last irrelevant comment: (7) One extreme WCS standard that we *could* put forward, and which *would* work in all circumstances is the following: (7.1) A list of ra, dec values, and a matched list of x,y values. Interpolate as you wish! (7.2) This standard would allow distortions of any kind, automatically includes the forwards and reverse transformations, does not need to piggy-back on the existing WCS TAN (or any other) undistorted standard, permits distortions of any order or character, permits the investigator to make the distortion finer in some parts of the image than others, etc. etc. It is not fully specified, of course, but a full specification would not be hard to write. (7.3) Implemented standards are better than non-implemented standards, so for now we still prefer SIP. David -- David W. Hogg - associate professor, NYU - http://cosmo.nyu.edu/hogg/ |
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