Robust Denoising Fukushima Endoscopic Videos

[ このビデオは東京電力によって公開された、福島第一原発の第5核融合炉の内部を映したものです。
我々は新しく考案したRobust PCA等を用いた新しいアルゴリズムを用いて、水滴や放射線等によるノイズを除去しました。

 http://nuclear.tamu.edu/~kurwitz/

The following videos were released by TEPCO. They show the inside of reactor 5 at Fukushima Daiichi. We processed these videos using new techniques such as Robust PCA to evaluate the algorithm's capabilities to separate background information from more dynamic information such as water droplets and radiation hits on the focal plane array. Thank you Julien, Yasuda-san and Tsuji-san for the translation.  ].

In Robust Denoise This! I wondered if there was a way to denoise the videos coming out of endoscopic visualization of the containment vessel of reactor 5 at Fukushima Daiichii. One of the impediment of videos being inserted in this area is clearly related to the radiation field and water droplets that render the video very noisy. We are here well outside the comfortable academic benchmarks used to figure out the quality of denoising algorithms. However, I am of the opinion that any of the Robust PCA or other advanced Matrix Factorization techniques can only be field tested with actual footages that have not been carefully prepared like these endoscopic shots. 

For this reason, Cable Kurwitz and I were thinking about what could be obtained from this sort of shots. Let us first realize that these endoscopic shots were performed on one of the least damaged reactor and so radiation issue for this survey would be more like what could be expected from a reactor that has gone through a  normal cold shutdown operation  

The GoDec solver was used for this preliminary trial. It performs a low rank decomposition added with a sparse and noisy component. We were wondering if the radiation field (mostly bleeps occurring at every frame at different locations) would be caught by the noisy component. By the way, they are not truly blips because the videos themselves seem to have been transform coded with MPEG: i.e every hit has become more like small crosses. We hypotethized that the droplets would mostly be in the sparse component so that the noisy component would provide a proxy for the radiation level seen by the endoscopic Focal Place Array. In other words, we could use the video also as radiation detector.. Here is the result so far from about 800 frames at 1 minutes into video 2:

Here is what we can see:

• The low rank component (1) is pretty nice and steady and seems to be able to catch different illuminations
• The noisy component (3) does indeed catch most of the the radiation hits but
• it also catches some of the droplet component (so the noisy component cannot be used right away as a proxy to the radiation level). 
• The sparse components (2) picks up most of the droplets 

Additional processing would need to be performed on the noisy component to catch only the radiation hit  component.





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