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

TL;DR

The paper introduces the STONE transform, a novel sensing framework that allows instant high-resolution reconstruction and subsequent enhancement of compressive measurements, enabling real-time video processing on embedded devices.

Contribution

It presents the STONE transform, combining conventional and compressive sensing for fast reconstruction and resolution enhancement, suitable for real-time applications.

Findings

Instant reconstruction at Nyquist rates across resolutions

Enhanced resolution using sparsity-based compressive methods

Real-time compressive video camera demonstration

Abstract

Compressed sensing enables the reconstruction of high-resolution signals from under-sampled data. While compressive methods simplify data acquisition, they require the solution of difficult recovery problems to make use of the resulting measurements. This article presents a new sensing framework that combines the advantages of both conventional and compressive sensing. Using the proposed \stone transform, measurements can be reconstructed instantly at Nyquist rates at any power-of-two resolution. The same data can then be "enhanced" to higher resolutions using compressive methods that leverage sparsity to "beat" the Nyquist limit. The availability of a fast direct reconstruction enables compressive measurements to be processed on small embedded devices. We demonstrate this by constructing a real-time compressive video camera.