4 ms·

This tool appears to be an open-source (and faster) replacement for Focus Magic, in that it allows the user to perform parameterized deconvolution. By that I m

by teuobk 14y ago

This tool appears to be an open-source (and faster) replacement for Focus Magic, in that it allows the user to perform parameterized deconvolution. By that I mean: if the blur kernel can be approximated by either a line or a filled circle, and you're willing to tweak the dimensions and angles of the blur kernel, this can do a decent job of recovering your photo. If the true blur kernel is more complicated -- perhaps a wavy line -- then you probably need a blind deconvolution tool, which this is not (yet?). If you're interested in blind deconvolution in general, Dr. Levin of MIT put together a nice overview paper a few years ago: http://www.wisdom.weizmann.ac.il/~levina/papers/deconvLevinEtalCVPR09.pdf http://www.wisdom.weizmann.ac.il/~levina/papers/deconvLevinE... (Disclaimer: I'm the developer of Blurity, a blind deconvolution product)

xfs 14y ago
Fascinating. I have tried to find methods to recover text from digitally blurred images but ended up doing research and survey on similar topics while not finding any available tool for the task. I still have several questions: - How well does the state of the art deblurring work with digital blur of known algorithms for forensic purposes? - How does blind deconvolution compete with some manual recovery processes done by experts, if there exist such manual methods? - Can approaches in blind deconvolution extend to techniques of resolution enhancing from a sequence of photos taken with the same parameters? - Are there researchers trying to integrate visual cognition frameworks into making deconvolution results more visually recognizable? I remember one somewhat related research was posted on HN: http://news.ycombinator.com/item?id=4241266 http://news.ycombinator.com/item?id=4241266 (and it happens to be coming from the same university as the paper you posted)
- teuobk 14y ago
  Good questions. My thoughts: - Are you asking about recovery of information that was intentionally blurred? If so, there have been some exciting results in this area in recent years. For example, it turns out that given reasonable priors on the underlying glyphs, it's possible to reconstruct even heavily blurred text. (e.g., http://dheera.net/projects/blur.php http://dheera.net/projects/blur.php ) That doesn't involve deblurring per se, since the goal is simply to find the glyphs (and combinations thereof) with maximum likelihood given the blurred text. Still, it's interesting, and similar techniques have been applied to super-resolution problems lately, where the approach is often called "hallucination." - Blind deconvolutions often are used by experts. However, it's possible to help things along if a glint exhibiting the blur of interest is visible in the photo. That is: if a bright dot of light is visible in the photo, it will be blurred too, and so in the blurred photo the point of light will look like the point spread function (the blur kernel), and that can then be extracted and used with a non-blind deconvolution approach to recover the latent sharp image. - Blind deconvolution and super-resolution are related problems, so advances in one might certainly help in the other. The research you cited makes use of image hallucination (mentioned above) as a key part of its super-resolution algorithm.

by teuobk 14y ago

xfs 14y ago

Fascinating. I have tried to find methods to recover text from digitally blurred images but ended up doing research and survey on similar topics while not finding any available tool for the task. I still have several questions: - How well does the state of the art deblurring work with digital blur of known algorithms for forensic purposes? - How does blind deconvolution compete with some manual recovery processes done by experts, if there exist such manual methods? - Can approaches in blind deconvolution extend to techniques of resolution enhancing from a sequence of photos taken with the same parameters? - Are there researchers trying to integrate visual cognition frameworks into making deconvolution results more visually recognizable? I remember one somewhat related research was posted on HN: http://news.ycombinator.com/item?id=4241266 http://news.ycombinator.com/item?id=4241266 (and it happens to be coming from the same university as the paper you posted)

teuobk 14y ago
Good questions. My thoughts: - Are you asking about recovery of information that was intentionally blurred? If so, there have been some exciting results in this area in recent years. For example, it turns out that given reasonable priors on the underlying glyphs, it's possible to reconstruct even heavily blurred text. (e.g., http://dheera.net/projects/blur.php http://dheera.net/projects/blur.php ) That doesn't involve deblurring per se, since the goal is simply to find the glyphs (and combinations thereof) with maximum likelihood given the blurred text. Still, it's interesting, and similar techniques have been applied to super-resolution problems lately, where the approach is often called "hallucination." - Blind deconvolutions often are used by experts. However, it's possible to help things along if a glint exhibiting the blur of interest is visible in the photo. That is: if a bright dot of light is visible in the photo, it will be blurred too, and so in the blurred photo the point of light will look like the point spread function (the blur kernel), and that can then be extracted and used with a non-blind deconvolution approach to recover the latent sharp image. - Blind deconvolution and super-resolution are related problems, so advances in one might certainly help in the other. The research you cited makes use of image hallucination (mentioned above) as a key part of its super-resolution algorithm.