Compressive Sensing (CS) is a new sensing modality, which compresses the signal being
acquired at the time of sensing. Signals can have sparse or compressible representation …

Discrete Fourier transform (DFT) implementation requires high computational resources and
time; a computational complexity of order O (N 2) for a signal of size N. Fast Fourier …

Abstract Internet of Things (IoT) systems cannot successfully realize the notion of ubiquitous
connectivity of everything if they are not capable to truly include 'multimedia things' …

Compressed-sensing reconstruction of still images and video sequences driven by
multihypothesis predictions is considered. Specifically, for still images, multiple predictions …

A number of techniques for the compressed sensing of imagery are surveyed. Various
imaging media are considered, including still images, motion video, as well as multiview …

A simple block-based compressed-sensing reconstruction for still images is adapted to
video. Incorporating reconstruction from a residual arising from motion estimation and …

This paper presents the design of a networked system for joint compression, rate control and
error correction of video over resource-constrained embedded devices based on the theory …

The compressive sensing (CS) theory indicates that robust reconstruction of signals can be
obtained from far fewer measurements than those required by the Nyquist–Shannon …

Compressive sensing (CS) has been widely studied and applied in many fields. Recently,
the way to perform secure compressive sensing (SCS) has become a topic of growing …

Image acquisition and communication in wireless sensor networks (WSNs) are key issues
for some applications that require image sensing. Lowering the sampling rate and reducing …