Two measurement matrix based nonuniform sampling for wireless sensor networks

Abstract

In nonuniform sampling based Compressed Sensing the DCT coefficients of an image block are scanned in zigzag order to form a single column vector. This column vector is divided into important and unimportant component. If same measurement matrix is used to measure the unimportant component of all blocks of an image, it results in large number of measurements. In this paper, a two measurement matrix based nonuniform sampling Compressed Sensing is proposed. The measurement matrix with less number of rows is used to measure the unimportant component of low frequency content blocks and the other measurement matrix with large number of rows is used to measure unimportant component of high frequency content blocks of the image. The simulated result shows that proposed method can produce 5% to 40% reduction in number of measurements than one measurement matrix based nonuniform sampling Compressed Sensing, enabling its use in wireless sensor networks.