There has been a lot of excitement around the use of denoising algorithms to allow reconstruction of microscopy images to allow data collection at very low light levels, thus allowing fast long-term timelapse imaging of samples that would otherwise suffer too much photodamage. Much of this work has been done by the Sedat lab and colleagues here, so I hear a lot about it . The algorithm they use comes from the work of Jerome Boulanger and Charles Kevrann, and apparently performs very well. However, it’s been hard for me to test because obtaining the software is relatively difficult.
Yesterday, a new ImageJ plugin for denoising was posted on the ImageJ mailing list. It’s called CANDLE-J, and a preprint describing it is here. I haven’t had a chance to try it yet, but the results reported in the preprint look promising, and it is freely available for download. Binaries for Mac and Linux are available as is the source code. I’m guessing building it on Windows won’t be too hard.
An earlier version that runs in Matlab is also available.
- M. Arigovindan, J.C. Fung, D. Elnatan, V. Mennella, Y.M. Chan, M. Pollard, E. Branlund, J.W. Sedat, and D.A. Agard, "High-resolution restoration of 3D structures from widefield images with extreme low signal-to-noise-ratio", Proceedings of the National Academy of Sciences, vol. 110, pp. 17344-17349, 2013. http://dx.doi.org/10.1073/pnas.1315675110
- P.M. Carlton, J. Boulanger, C. Kervrann, J. Sibarita, J. Salamero, S. Gordon-Messer, D. Bressan, J.E. Haber, S. Haase, L. Shao, L. Winoto, A. Matsuda, P. Kner, S. Uzawa, M. Gustafsson, Z. Kam, D.A. Agard, and J.W. Sedat, "Fast live simultaneous multiwavelength four-dimensional optical microscopy", Proceedings of the National Academy of Sciences, vol. 107, pp. 16016-16022, 2010. http://dx.doi.org/10.1073/pnas.1004037107