Designing for Compressive Sensing: Compressive Art, Camouflage, Fonts, and Quick Response Codes

Report No. ARL-TR-8281
Authors: Michael L Don
Date/Pages: January 2018; 30 pages
Abstract: Compressive sensing is a signal processing technique that takes advantage of a signal's sparsity to reduce sampling requirements. This can be used to improve system resolution, frame rate, power consumption, and memory usage. Most compressive sensing research has focused on developing sensing systems and demonstrating their performance sensing preexisting objects. Little research has been directed toward designing the objects being sensed. This report addresses this overlooked area. Simple examples are shown demonstrating the advantage of modifying an object's sparsity to increase or decrease compressive sensing performance. This leads to more complex object recognition examples where the object's sparsity must be balanced against its quality for optimal performance. In these cases, simulation results show that there are significant gains when one designs for compressive sensing.
Distribution: Approved for public release
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Last Update / Reviewed: January 1, 2018