Reply by Tom Kinter November 11, 20042004-11-11
Hi,

If your main goal is just to improve these images you might take a look at a very nice tool that has a demo: Neat Image at http://www.neatimage.com
It has saved the day on some of my photographs.

Tom

In article <cmofj5$5dn$1@news.Stanford.EDU>, "kiki" <lunaliu3@yahoo.com> writes:
> >I obtained some pictures using camera. It looks to me there are some >additive noise that was added to all image pixel components: from what I've >observed, there are many small fluctuations/peaks/spikes of height 10-30, >while the useful image region has values about 300. > >I am afraid that such noise has also been added to the useful image region, >so the images have been universally shifted by 10-30 noise values. How can I >estimate the noise and substract the noise value from those useful image >region? Can I take the average of 10 and 30 and get 20, and then substract >the 20 from all images? > >Any better ideas? >
Tom ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tom Kinter tmk@mayo.edu 507-284-4981 Mayo Foundation Rochester MN 55905 USA http://www.mayo.edu/ultrasound Tom's Place http://www.tkinter.smig.net ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Reply by Martin Leese November 11, 20042004-11-11
kiki wrote:
> Hi all, > > I obtained some pictures using camera. It looks to me there are some > additive noise that was added to all image pixel components: from what I've > observed, there are many small fluctuations/peaks/spikes of height 10-30, > while the useful image region has values about 300. > > I am afraid that such noise has also been added to the useful image region, > so the images have been universally shifted by 10-30 noise values. How can I > estimate the noise and substract the noise value from those useful image > region? Can I take the average of 10 and 30 and get 20, and then substract > the 20 from all images? > > Any better ideas?
Image acquisition is everything. Take several images of the same scene and then average them together. The random noise will be different in each image, and so will average away. This is called ensemble averaging, and there is no better way to reduce random noise in an image. -- Regards, Martin Leese E-mail: please@see.Web.for.e-mail.INVALID Web: http://members.tripod.com/martin_leese/
Reply by Pat November 9, 20042004-11-09
kiki wrote:
> Hi all, > > I obtained some pictures using camera. It looks to me there are some > additive noise that was added to all image pixel components: from what I've > observed, there are many small fluctuations/peaks/spikes of height 10-30, > while the useful image region has values about 300. > > I am afraid that such noise has also been added to the useful image region, > so the images have been universally shifted by 10-30 noise values. How can I > estimate the noise and substract the noise value from those useful image > region? Can I take the average of 10 and 30 and get 20, and then substract > the 20 from all images? > > Any better ideas? > > thanks a lot > >
Hi, If you are certain that it is unwanted additive noise, then take all values that fall in that range and substitute the 'true' value. I saw that one many years ago on some pictures of saturn and the results were stunning. They called it something like a stairstep function. The output for some range of values is a single value. If you encounter a soft gradient type of image, all bets are off. Pat
Reply by Johan Carlson November 8, 20042004-11-08
If the noise isn't simply additive white gaussian noise, but actually 
exhibits some systematic behavior, there might be a way out if you can 
find a way to model the statistics of your noise. Now, that's gonna 
require some hardcore signal processing, and I'm not sure that's your 
game of choice....

/Johan

Jerry Avins wrote:

> kiki wrote: > > >>"Jerry Avins" <jya@ieee.org> wrote in message > > > ... > > >>Hi Jerry, >> >>The problem is that I don't know what should those shifts be and what should >>the correct pixel values be... >> >>I just see there are small fluctuation/spikes/peaks everywhere, but are >>locally rapid fluctuation. >> >>How do I do that? > > > Take two pictures of a blank wall without moving the camera. Subtract > one from the other. Don't rely on the camera not moving at all if the > result isn't mostly zero, but shift one and two pixels in each direction > (15 total shifted positions in all). If any of those are mostly zero, > you have a correction mask. Otherwise, look at the spectrum of the > noise. If there is a low-pass filter that can block it without degrading > the picture too much, good. If not, that's hard luck. To filter, you > needn't necessarily work with the FT of the image. The chances are that > a 3 by 3 kernel (or at most a 5 by 5 with the corners missing) will do. > > Jerry
Reply by Jerry Avins November 8, 20042004-11-08
kiki wrote:

> "Jerry Avins" <jya@ieee.org> wrote in message
...
> Hi Jerry, > > The problem is that I don't know what should those shifts be and what should > the correct pixel values be... > > I just see there are small fluctuation/spikes/peaks everywhere, but are > locally rapid fluctuation. > > How do I do that?
Take two pictures of a blank wall without moving the camera. Subtract one from the other. Don't rely on the camera not moving at all if the result isn't mostly zero, but shift one and two pixels in each direction (15 total shifted positions in all). If any of those are mostly zero, you have a correction mask. Otherwise, look at the spectrum of the noise. If there is a low-pass filter that can block it without degrading the picture too much, good. If not, that's hard luck. To filter, you needn't necessarily work with the FT of the image. The chances are that a 3 by 3 kernel (or at most a 5 by 5 with the corners missing) will do. Jerry -- Engineering is the art of making what you want from things you can get. &#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;
Reply by kiki November 8, 20042004-11-08
"Jerry Avins" <jya@ieee.org> wrote in message 
news:2v9vjoF2i0obaU3@uni-berlin.de...
> kiki wrote: > >> Hi all, >> >> I obtained some pictures using camera. It looks to me there are some >> additive noise that was added to all image pixel components: from what >> I've >> observed, there are many small fluctuations/peaks/spikes of height 10-30, >> while the useful image region has values about 300. >> >> I am afraid that such noise has also been added to the useful image >> region, >> so the images have been universally shifted by 10-30 noise values. How >> can I >> estimate the noise and substract the noise value from those useful image >> region? Can I take the average of 10 and 30 and get 20, and then >> substract >> the 20 from all images? >> >> Any better ideas? >> >> thanks a lot > > Are the individual pixel shifts nearly the same in each of several images? > > Jerry > -- > Engineering is the art of making what you want from things you can get. > &#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;
Hi Jerry, The problem is that I don't know what should those shifts be and what should the correct pixel values be... I just see there are small fluctuation/spikes/peaks everywhere, but are locally rapid fluctuation. How do I do that? Thanks a lot!
Reply by Jerry Avins November 8, 20042004-11-08
kiki wrote:

> Hi all, > > I obtained some pictures using camera. It looks to me there are some > additive noise that was added to all image pixel components: from what I've > observed, there are many small fluctuations/peaks/spikes of height 10-30, > while the useful image region has values about 300. > > I am afraid that such noise has also been added to the useful image region, > so the images have been universally shifted by 10-30 noise values. How can I > estimate the noise and substract the noise value from those useful image > region? Can I take the average of 10 and 30 and get 20, and then substract > the 20 from all images? > > Any better ideas? > > thanks a lot
Are the individual pixel shifts nearly the same in each of several images? Jerry -- Engineering is the art of making what you want from things you can get. &#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;&#4294967295;
Reply by kiki November 8, 20042004-11-08
Hi all,

I obtained some pictures using camera. It looks to me there are some 
additive noise that was added to all image pixel components: from what I've 
observed, there are many small fluctuations/peaks/spikes of height 10-30, 
while the useful image region has values about 300.

I am afraid that such noise has also been added to the useful image region, 
so the images have been universally shifted by 10-30 noise values. How can I 
estimate the noise and substract the noise value from those useful image 
region? Can I take the average of 10 and 30 and get 20, and then substract 
the 20 from all images?

Any better ideas?

thanks a lot