Timeline for Rotationally-Invariant 2D Discrete Transforms
Current License: CC BY-SA 3.0
25 events
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| Apr 13, 2016 at 18:42 | history | edited | Amir Sagiv | CC BY-SA 3.0 |
I don't think the no-tag should be there
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| Apr 25, 2012 at 2:29 | answer | added | Cobalt60 | timeline score: 1 | |
| Feb 23, 2012 at 14:55 | answer | added | Jean-Luc Bouchot | timeline score: 0 | |
| Jan 10, 2011 at 15:55 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 10, 2011 at 15:41 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 10, 2011 at 15:34 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 10, 2011 at 15:11 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 10, 2011 at 1:28 | comment | added | Igor Rivin | Averaging the $O(2)$ orbit is quite clearly invariant only with respect to rotations, and it will compress wonderfully, but it is, sadly, very lossy (I mentioned it because all the compression algorithms stemming from the transforms you mention are lossy...) | |
| Jan 9, 2011 at 14:56 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 9, 2011 at 14:41 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
edited body; deleted 10 characters in body; Post Made Community Wiki
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| Jan 9, 2011 at 14:39 | comment | added | user12103 | @Noah, we can assume that our transforms work in the same spirit that other discrete transforms work (e.g. DTFT), i.e. the disk has a finite number of samples from a continuous disk. | |
| Jan 9, 2011 at 14:28 | comment | added | Noah Stein | @AV80: In what sense is the signal "discrete" then? | |
| Jan 9, 2011 at 14:28 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 9, 2011 at 14:21 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 9, 2011 at 14:10 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 9, 2011 at 14:08 | comment | added | user12103 | @Dirk, the "standard" representation of a 2D image in computer vision is a matrix, but for our purposes we can assume that the input signal is a disk of known radius. | |
| Jan 9, 2011 at 14:06 | comment | added | user12103 | @Igor, I updated the question. We can assume rotations around the center point of a disk that holds the 2D signal. Would averaging the $O(2)$ orbit be invariant to rotations only? | |
| Jan 9, 2011 at 12:06 | comment | added | Dirk | It seems to me that "2D discrete transform" does not go well with "arbitraty 2D rotation". Do you assume that your objects to be rotated are matrices in some sense? Then only rotation about 90° make sense (without interpolation)... | |
| Jan 9, 2011 at 3:57 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 9, 2011 at 2:06 | comment | added | Igor Rivin | Rotations about what? If you pick a basepoint in advance, then averaging the $O(2)$ orbit compresses the signal A LOT. | |
| Jan 8, 2011 at 21:34 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 8, 2011 at 19:48 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 8, 2011 at 19:40 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 8, 2011 at 19:02 | history | edited | Amelio Vazquez-Reina | CC BY-SA 2.5 |
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| Jan 8, 2011 at 18:56 | history | asked | Amelio Vazquez-Reina | CC BY-SA 2.5 |