Compressed Sensing: A Faster Noiselet Transform and a Hybrid Reconstruction Algorithm

Laurent Jacques mentioned to me that he has built an even faster Noiselet transform than the one he sent me earlier, four times faster actually. This new version is located in the Codes section of his website. I am also pointing to that site from here.

I went to a presentation this afternoon by Sebastien Bourguignon (mentioned here before) in what amounts to inpainting in the frequency domain and discovered that he had already tried successfully something similar to the (now infamous :-) ) boosted algorithm suggested earlier. It is an hybrid algorithm that has a reweighted L1 algorithm as a second stage. It seems to me that with the large number of reconstruction methods, one could empirically build something that is very robust in the same way the Bellkor team did with the Netflix prize. During the Q/A, somebody suggested we look at SMLR, a greedy algorithm originally used in geophysics, I'll have to look into it.


Credit: NASA/JPL/University of Arizona, Proposed MSL Landing Site in Eberswalde Crater (PSP_007481_1560)