Ok, what about gaussian blur?
It's all a blur
31–40 of 70 posts
Re: It's all a blur
#32>But then, it’s not wrong to scratch your head. Blurring amounts to averaging the underlying pixel values. If you average two numbers, there’s no way of knowing if you’ve started with 1 + 5 or 3 + 3. In both cases, the arithmetic mean is the same and the original information appears to be lost. So, is the advice wrong?
Well, if you have a large enough averaging window (like is the case with bluring letters) they have constraints (a fixed number of shapes) information for which is partly retained.
Not very different from the information retained in minesweeper games.
Re: It's all a blur
#33Those unblurring methods look "amazing" like that but they are just very fragile, add even a modicum of noise to the blurred image and the deblurring will almost certainly completely fail, this is well-known in signal-processing
Did you see the part where he saved with more and more lossy compression and showed that it still was recoverable?
Re: It's all a blur
#34Can this be applied to camera shutter/motion blur, at low speeds the slight shake of the camera produces this type of blur. This is usually resolved with IBIS to stabilize the sensor.
Absolutely, Photoshop has it:
https://helpx.adobe.com/photoshop/using/reduce-camera-shake-...
Or... from the note at the top, had it? Very strange, features are almost never removed. I really wonder what the architectural reason was here.
Re: It's all a blur
#35Can this be applied to camera shutter/motion blur, at low speeds the slight shake of the camera produces this type of blur. This is usually resolved with IBIS to stabilize the sensor.
The ability to reverse is very dependent on the transformation being well known, in this case it is deterministic and known with certainty. Any algorithm to reverse motion blur will depend on the translation and rotation of the camera in physical space, and the best the algorithm could do will be limited by the uncertainty in estimating those values. If you apply a fake motion blur like in photoshop or after effects…
> and the best the algorithm could do will be limited by the uncertainty in estimating those values
That's relatively easy if you're assuming simple translation and rotation (simple camera movement), as opposed to a squiggle movement or something (e.g. from vibration or being knocked). Because you can simply detect how much sharper the image gets, and hone in on the right values.
Re: It's all a blur
#36One salient point not touched on here, is that an awful lot of the time, the things folks are blurring out specifically is text. And since we know an awful lot about what text ought to look like, we have a lot more information to guide the reconstruction...
Good point, though you have to beware that text-aware image enhancement sometimes replaces characters with what it thinks is a more likely character from context.
I've seen my phone camera's real-time viewfinder show text on a sign with one letter different from the real sign. If I wasn't looking at the sign at the same time, I might not have noticed the synthetic replacement.
Re: It's all a blur
#37reminds me of the guy who used the photoshop swirl effect to mask his face in csam he produced, who was found out when someone just undid the swirl
This is the case I always think of when it comes to reversing image filters.
Re: It's all a blur
#38Sorry but this post is the blind leading the blind, pun intended. Allow me to explain, I have a DSP degree. The reason the filters used in the post are easily reversible is because none of them are binomial (i.e. the discrete equivalent of a gaussian blur). A binomial blur uses the coefficients of a row of Pascal's triangle, and thus is what you get when you repeatedly average each pixel with its neighbor (in 1D). Wh…
> Sorry but this post is the blind leading the blind, pun intended. Allow me to explain, I have a DSP degree.
FWIW, this does not read as constructive.
Re: It's all a blur
#39In practice unblurring (deconvolution) doesn't really work as well as you'd hope because it is usually blind (you don't know the blur function), and it is ill-conditioned, so any small mistakes or noise get enormously amplified.
Re: It's all a blur
#40One salient point not touched on here, is that an awful lot of the time, the things folks are blurring out specifically is text. And since we know an awful lot about what text ought to look like, we have a lot more information to guide the reconstruction...
Good point, though you have to beware that text-aware image enhancement sometimes replaces characters with what it thinks is a more likely character from context. I've seen my phone camera's real-time viewfinder show text on a sign with one letter different from the real sign. If I wasn't looking at the sign at the same time, I might not have noticed the synthetic replacement.
>> sometimes replaces characters with what it thinks is a more likely character from context
Like the JBIG2 algorithm used in a zero click PDF-as-GIF exploit in iMessage a while back: https://projectzero.google/2021/12/a-deep-dive-into-nso-zero...
The vulnerability of that algorithm to character-swapping caused incorrect invoices, incorrect measurements in blueprints, incorrect metering of medicine, etc. https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres...