Sequential adaptive compressed sampling via Huffman codes by Akram Aldroubi, Haichao Wang, Kourosh Zarringhalam. The abstract reads:
There are two main approaches in compressed sensing: the geometric approach and the combinatorial approach. In this paper we introduce an information theoretic approach and use results from the theory of Huffman codes to construct a sequence of binary sampling vectors to determine a sparse
signal. Unlike other approaches, our approach is adaptive in the sense that each sampling vector depends on the previous sample. The number of measurements we
need for a k-sparse vector in n-dimensional space is no more than O(k log n) and the reconstruction is O(k).
3.2 Non-Deterministic and Adaptive Measurement codes/matrices as mentioned here (as well as new ones).
In our experiment, we use the vertical binary stripe patterns as the coded light pattern. Each frame has 128 stripes. The stripes are randomly assigned to be 0 (black) or 1 (white) according to Bernoulli distribution (with p=0.5). We also tried Hadamard codes and found that the Bernoulli random code is better.
I am sure they will also be able to use adaptive measurements at some point in time.
Image Credit: NASA/JPL/Space Science Institute, Have you ever seen star shining through Saturn's ring ? W00050600.jpg was taken on October 28, 2008 and received on Earth October 29, 2008.