Well-known compressed sensing (CS) is widely used in image acquisition and
reconstruction. However, accurately reconstructing images from measurements at low …

The convolutional neural network (CNN)-based reconstruction methods have dominated the
compressive sensing (CS) in recent years. However, existing CNN-based approaches show …

Aiming at the security and efficiency problems in the process of image transmission, an
image compression–encryption scheme based on 2D compressive sensing and …

Among the wireless body area network (WBAN) scarce resources, energy resource is an
essential resource on which most of the WBAN biomedical devices activities depend upon …

Image compressed sensing (ICS) has been extensively applied in various imaging domains
due to its capability to sample and reconstruct images at subNyquist sampling rates. The …

A measurement matrix is essential to compressed sensing frameworks. The measurement
matrix can establish the fidelity of a compressed signal, reduce the sampling rate demand …

The application of multimedia sensors is widespread, and people need to transmit images
more securely and efficiently. In this paper, an image transmission scheme based on two …

Wireless Multimedia Sensor Networks (WMSN) hold the key to unlocking the next
generation of video surveillance applications. They operate under energy-constrained …

Compressed sensing exploits the signal's sparsity by non-uniform sampling to achieve high-
quality signal reconstruction at low sampling rates. This work aims to show the efficient …

The development of measurement matrices remains a pivotal focus within the domain of
compressed sensing theory. This paper introduces an innovative methodology for the …