A Virtual Instrument for Compressive Sensing of multimedia signals

Abstract

Compressive Sensing (CS) is currently a very popular signal acquisition approach. It provides an alternative way of signal sampling which is based on a small random set of measurements. The entire signal can be reconstructed from the measurements with high accuracy by using very complex mathematical algorithms if the certain conditions are met. Various algorithms for CS reconstruction have been proposed for different types of signals and different application requirements. In this paper, several commonly used algorithms for one-dimensional (1D) and two-dimensional (2D) signals reconstruction are implemented within the Virtual Instrument for CS signals reconstruction. The Virtual Instrument is a user-friendly tool that provides efficient analysis of signals, using different algorithms and variety of options and parameters. It includes different multimedia test signals (both 1D and 2D signals), but also there is an option for user-defined signals.