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47364Re: What is the actual Field of View?

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  • engstrom_henrik
    Jan 10, 2011
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      --- In PanoToolsNG@yahoogroups.com, Erik Krause <erik.krause@...> wrote:
      > Am 08.01.2011 00:03, schrieb engstrom_henrik:
      > > And when transforming an image in a non-linear fashion (e.g.
      > > stitching) you will get worse apparent resolution, something one
      > > simply cannot afford for this type of surveillance. This was easy to
      > > see with the naked eye in this case, the images were far from the
      > > original sharpness.
      > What stitching engine did you use? If you don't scale up a single
      > transformation step (and panotools combines all necessary warping into
      > one step) should not cause any noticeable image degradation. At least
      > not if you use one of the better interpolation algorithms.
      > --
      > Erik Krause
      > http://www.erik-krause.de

      I do not know exactly how the stitching was performed in that particular case, it's the IPR of another company. I am guessing something like bicubic interpolation (one-step).

      Panotools have got much more advanced, near sinc, blending operations. But to my knowledge they all remove some high-frequency information. In this particular application, it can be beneficial to be able to read text on a vehicle. And this is where the transformations may hurt performance, since the text contains quite high-frequency edges. Another aspect is the ability to detect small vehicles far away.

      But I really would like to be proven wrong here, it could solve a lot of problems. I have uploaded some test images, I hope they can be viewed correctly;


      - 01_hf_pattern is an extremely high-frequency pattern (256x256 pixels) used as reference.
      - 02_rotate_1_0 is the reference pattern rotated 1.0 degrees in GIMP (possibly bicubic?).
      - 03_ hf_pattern_zoom is the top-left 64x64 pixels zoomed-in.
      - 04_ rotate_1_0_zoom is the top-left 64x64 pixels zoomed-in.

      It tries to illustrate effects of transformation of a high-frequency image data. It is an extreme case, but still shows that information may get completely lost in the process. Can a more advanced interpolator perform much better in this case?

      If one uses for example 10-15 MP cameras one may not think of this as a problem. Here, typically ~1 MP cameras are used, and it can be very noticeable.

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