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> license plate that was too small in the original image to see the letters of I did mention that better quality photos are available. And I did show that ther

by alister 14y ago

> license plate that was too small in the original image to see the letters of I did mention that better quality photos are available. And I did show that there are at least 2 photos of the same license plate -- there are probably more. In the photos printed in books, the license plate looks like the last couple lines of the Snellen eye chart in the original article -- i.e. it's quite blurry, but the super-resolution nethod was able to resolve it. > it guesses at what the blown up image should look like based on an examination of other features already in the image, with some expectation that shapes and textures will be similar in different parts of the image and at different scales It is true that there are no license plates at different scales in the same image. But are you quite certain that the technique cannot be applied across a range of photographs? That is, couldn't photos of license plates of the same type (and hence with exactly the same font) at different scales taken by the same photographic process on the same day in the same conditions have the same "fractal nature" that could be exploited to improve the resolution of the target photo? Let me put it another way: Suppose I cut up the Snellen eye chart into 6 equal pieces. Now I have 6 photos. Clearly, 5 of those photos can be used to improve the resolution of the 6th. Is there some principle at work here that says that for super-resolution to work, all data must come from a single original photo?

jacobolus 14y ago
If you had several pictures of the same license plate, each of which was big enough to get meaningful information from but just barely too small to make out the letters when you blew it up with a regular bicubic interpolation + gaussian sharpening step, then you might be able to figure out more than you previously could. It seems quite unlikely to me, but go ahead and try it. If you look carefully, it’s actually possible to make meaningful guesses at the letters in the eye chart just as well in the bicubic version as in the “SR” version.
- ricardobeat 14y ago
  Did we look at the same chart? The characters in that last line are 3 or 4 pixels tall. I just did an experiment and 80% of guesses were wrong. There is just not enough information, but this method can still decode them.
  - rcthompson 14y ago
    Unfortunately, you don't know that the algorithm got the right answer for the letters on the bottom row. You'd have to try it on an image where you already knew the answers. Other comment threads note the there are lots of errors on that last line in the eye chart. Again, you can't recover more information than is in the image. When multiple characters look identical when scaled down, no algorithm can recover them reliably.
    - ricardobeat 14y ago
      It didn't, but it got pretty close (16 out of 22). Here's that one in better resolution: http://upload.wikimedia.org/wikipedia/commons/b/b8/Eye-chart.jpg http://upload.wikimedia.org/wikipedia/commons/b/b8/Eye-chart...
      - rcthompson 14y ago
        Well, with a 16/22 chance of getting a letter right, that gives a 15% chance of correctly reading a 6-letter license plate correctly. Of course that can be improved with more training, but I don't think it'll ever get high enough to make any dent in the conspiracy theories. Then again, maybe they'll all want to believe in the CSI-style zoom/enhance magic.
  - ChrisClark 14y ago
    The authors explained the chart, it only works because it looks across the whole chart for similar parts and recreates the smaller characters using the data it finds in the larger ones. So you would need a couple larger images of the licence plate too. Information cannot be created from nothing, the algorithm sees that the chart seems to be repeating a similar image over and over, so it guesses the best fit for those images on the bottom lines. They might even be completely wrong, for example, is it really a D and not an O?
    - ricardobeat 14y ago
      Yes. That's why the author mentions using other plate images from the time, having the same typeface, to seed the algorithm. He mentions that higher res photographs exist, which might yield a plate image of a similar resolution to that chart's smallest characters. He is not asking for magic, and it's obviously not "creating information from nothing". No one here is stupid. It's "matching low-density patterns to correlated high-density ones", which you already know if you read the article. Maybe there isn't enough data at all to do it - I don't have access to these images to know better, but that doesn't make the idea any less reasonable.

by alister 14y ago

jacobolus 14y ago

If you had several pictures of the same license plate, each of which was big enough to get meaningful information from but just barely too small to make out the letters when you blew it up with a regular bicubic interpolation + gaussian sharpening step, then you might be able to figure out more than you previously could. It seems quite unlikely to me, but go ahead and try it. If you look carefully, it’s actually possible to make meaningful guesses at the letters in the eye chart just as well in the bicubic version as in the “SR” version.

ricardobeat 14y ago
Did we look at the same chart? The characters in that last line are 3 or 4 pixels tall. I just did an experiment and 80% of guesses were wrong. There is just not enough information, but this method can still decode them.
- rcthompson 14y ago
  Unfortunately, you don't know that the algorithm got the right answer for the letters on the bottom row. You'd have to try it on an image where you already knew the answers. Other comment threads note the there are lots of errors on that last line in the eye chart. Again, you can't recover more information than is in the image. When multiple characters look identical when scaled down, no algorithm can recover them reliably.
  - ricardobeat 14y ago
    It didn't, but it got pretty close (16 out of 22). Here's that one in better resolution: http://upload.wikimedia.org/wikipedia/commons/b/b8/Eye-chart.jpg http://upload.wikimedia.org/wikipedia/commons/b/b8/Eye-chart...
    - rcthompson 14y ago
      Well, with a 16/22 chance of getting a letter right, that gives a 15% chance of correctly reading a 6-letter license plate correctly. Of course that can be improved with more training, but I don't think it'll ever get high enough to make any dent in the conspiracy theories. Then again, maybe they'll all want to believe in the CSI-style zoom/enhance magic.
- ChrisClark 14y ago
  The authors explained the chart, it only works because it looks across the whole chart for similar parts and recreates the smaller characters using the data it finds in the larger ones. So you would need a couple larger images of the licence plate too. Information cannot be created from nothing, the algorithm sees that the chart seems to be repeating a similar image over and over, so it guesses the best fit for those images on the bottom lines. They might even be completely wrong, for example, is it really a D and not an O?
  - ricardobeat 14y ago
    Yes. That's why the author mentions using other plate images from the time, having the same typeface, to seed the algorithm. He mentions that higher res photographs exist, which might yield a plate image of a similar resolution to that chart's smallest characters. He is not asking for magic, and it's obviously not "creating information from nothing". No one here is stupid. It's "matching low-density patterns to correlated high-density ones", which you already know if you read the article. Maybe there isn't enough data at all to do it - I don't have access to these images to know better, but that doesn't make the idea any less reasonable.