Title :
The STOne Transform: Multi-Resolution Image Enhancement and Compressive Video
Author :
Goldstein, Tom ; Lina Xu ; Kelly, Kevin F. ; Baraniuk, Richard
Author_Institution :
Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA
Abstract :
Compressive sensing enables the reconstruction of high-resolution signals from under-sampled data. While the compressive methods simplify data acquisition, they require the solution of difficult recovery problems to make use of the resulting measurements. This paper presents a new sensing framework that combines the advantages of both the conventional and the compressive sensing. Using the proposed sum-to-one transform, the measurements can be reconstructed instantly at the Nyquist rates at any power-of-two resolution. The same data can then be enhanced to higher resolutions using the compressive methods that leverage sparsity to beat the Nyquist limit. The availability of a fast direct reconstruction enables the compressive measurements to be processed on small embedded devices. We demonstrate this by constructing a real-time compressive video camera.
Keywords :
compressed sensing; data acquisition; image enhancement; image reconstruction; image resolution; transforms; video signal processing; Nyquist limit; Nyquist rate; STOne transform; compressive measurements; compressive sensing; compressive video camera; data acquisition; high-resolution signal reconstruction; multiresolution image enhancement; power-of-two resolution; small embedded devices; sum-to-one transform; Cameras; Image coding; Image reconstruction; Image resolution; Sensors; Streaming media; Transforms; Mathematics; compressed sensing; sampling methods;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2015.2474697