Thanks for the reply. So does it mean that in your “Mean-standard deviation” curve, there is no “FPN regime” as shown in Janesick’s PTC plot, i.e., the regime with slope=1? Since you avoid FPN in your calculation? Just want to double check:-)

Best,

Dengyu

]]>In my descriptions, I Always calculate the noise along multiple frames for each pixel. In this way I can avoid any FPN in my calculation. The FPN calculation/measurement is another characterization.

Albert.

]]>Thanks for your quick response. So if I want to calculate the temporal noise for the whole image sensor area. Can I calculate the standard deviation along multiple frames for each pixel, and then average the whole area?

Another question is that I found in Janesick’s book, for the “mean-standard deviation” method, the total noise includes FPN noise, but for the “mean-variance” method, the noise is just temporal noise. However, in your descriptions, both methods seems like have the same temporal noise, is it different from Janesick’s description?

Best,

Dengyu

]]>I do calculate the temporal noise of EACH pixel by calculating the standard deviation of all values of ONE particular pixel in multiple frames. If you take only the values of ONE pixel into account you avoid the FPN, because you do not include the content of neighbouring pixels. This method can be repeated for every pixel of the image.

Success, Albert. ]]>

First thank you so much for posting the “How to Measure” series, I learned a lot from this. I hope I can also attend one of those “hands on” workshops in US also.

I have a question about the total temporal noise. I took a look of Jim Janesick’s PTC book. I found that in his book, the total noise includes read noise, shot noise and FPN noise. But here based on the equation, the total temporal noise seems don’t contain FPN noise. In Janesick’s book, he use “total noise” for “Mean-standard deviation” plot and “temporal noise variance” for “mean-variance” plot. So in your case, why the total noise doesn’t have FPN component? And how do you calculate the total temporal noise from captured images? Is it calculated as the squre root of variance of all the pixels?

Thanks,

Dengyu

]]>ps. prof. Jan v.d. Spiegel is with Univ. of Pennsylvania, i think. One of my MSc’s officemates in EI Lab, Chengjie Zuo, became a PhD student in his group in Univ.Penn. after graduating from TU Delft in 2006. Very small world!

]]>Well I thought I clearly understood that the pixel is using 2 PD’s, one for the short exposure and one for the two short multiplexed exposures. If that is the case I think the pixel needs to have at least 2 FD nodes, because the multiplexed sampling (by means of 1 PD) needs two storage nodes to store and accumulate the collected charge. But once these two signals are readout, the FD nodes are becoming available for reading the “full-length” exposure. So I think 2 PDs + 2 FDs can do the job. Whether this is also what is used in the ST pixel remains a question mark. Hopefully we will soon get the answer at one or another technical conference. Regards, Albert. ]]>