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Compressed sensing enables the reconstruction of high-resolution signals fromunder-sampled data. While compressive methods simplify data acquisition, theyrequire the solution of difficult recovery problems to make use of theresulting measurements. This article presents a new sensing framework thatcombines the advantages of both conventional and compressive sensing. Using theproposed \stone transform, measurements can be reconstructed instantly atNyquist rates at any power-of-two resolution. The same data can then be"enhanced" to higher resolutions using compressive methods that leveragesparsity to "beat" the Nyquist limit. The availability of a fast directreconstruction enables compressive measurements to be processed on smallembedded devices. We demonstrate this by constructing a real-time compressivevideo camera.

The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video