The Chaotic Measurement Matrix for Compressed Sensing

How to construct a measurement matrix with good performance and easy hardware implementation is the core research problem in compressed sensing. In this paper, we present a simple and efficient measurement matrix named Incoherence Rotated Chaotic (IRC) matrix. We take advantage of the well pseudorandom of chaotic sequence, introduce the concept of the incoherence factor and rotation, and adopt QR decomposition to obtain the IRC measurement matrix which is suited for sparse reconstruction. Simulation results demonstrate IRC matrix has a better performance than Gaussian random matrix, Bernoulli random matrix and other state-of-the-art measurement matrices. Thus it can efficiently work on both natural image and remote sensing image.