Medical image encryption based on biometric keys and lower-upper decomposition with partial pivoting.

The security of medical image transmission in telemedicine is very important to patients' privacy and health. A new asymmetric medical image encryption scheme is proposed. The medical image is encrypted by two spiral phase masks (SPM) and the lower-upper decomposition with partial pivoting, where the SPM is generated from the iris, chaotic random phase mask, and amplitude truncated spiral phase transformation.

Multi-View Image Denoising Using Convolutional Neural Network.

In this paper, we propose a novel multi-view image denoising algorithm based on convolutional neural network (MVCNN). Multi-view images are arranged into 3D focus image stacks (3DFIS) according to different disparities. The MVCNN is trained to process each 3DFIS and generate a denoised image stack that contains the recovered image information for regions of particular disparities.

Unified and accurate diffraction calculation between two concentric cylindrical surfaces.

A unified and accurate fast diffraction calculation between a pair of concentric cylindrical surfaces is proposed. Analysis of the obliquity factor shows that the physical meaning of it is the projection of the unit complex amplitude in the propagation direction onto the outer normal of the observation point. Therefore, a unified and accurate diffraction calculation formula for both inside-out and outside-in propagation models is achieved.

Wireless Sensor Array Network DoA Estimation from Compressed Array Data via Joint Sparse Representation.

A compressive sensing joint sparse representation direction of arrival estimation (CSJSR-DoA) approach is proposed for wireless sensor array networks (WSAN). By exploiting the joint spatial and spectral correlations of acoustic sensor array data, the CSJSR-DoA approach provides reliable DoA estimation using randomly-sampled acoustic sensor data. Since random sampling is performed at remote sensor arrays, less data need to be transmitted over lossy wireless channels to the fusion center (FC), and the expensive source coding operation at sensor nodes can be avoided.

Estimation of low-altitude moving target trajectory using single acoustic array.

An acoustic-signature based method of estimating the flight trajectory of low-altitude flying aircraft that only requires a stationary microphone array is proposed. This method leverages the Doppler shifts of engine sound to estimate the closest point of approach distance, time, and speed. It also leverages the acoustic phase shift over the microphone array to estimate the direction of arrival of the target.

Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing.

Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end.

Evaluation of wireless sensor networks (WSNs) for remote wetland monitoring: design and initial results.

Here, we describe and evaluate two low-power wireless sensor networks (WSNs) designed to remotely monitor wetland hydrochemical dynamics over time scales ranging from minutes to decades. Each WSN (one student-built and one commercial) has multiple nodes to monitor water level, precipitation, evapotranspiration, temperature, and major solutes at user-defined time intervals. Both WSNs can be configured to report data in near real time via the internet.