Regularized multiframe super-resolution image reconstruction using linear and nonlinear filters

The primary goal of the multiframe super-resolution image reconstruction is to produce an image with a higher resolution by integrating information extracted from a set of corresponding images with low resolution, which is used in various fields. However, super-resolution image reconstruction approaches are typically affected by annoying restorative artifacts, including blurring, noise, and staircasing effect. Accordingly, it is always difficult to balance between smoothness and edge preservation. In this paper, we intend to enhance the efficiency of multiframe super-resolution image reconstruction in order to optimize both analysis and human interpretation processes by improving the pictorial information and enhancing the automatic machine perception. As a result, we propose new approaches that firstly rely on estimating the initial high-resolution image through preprocessing of the reference low-resolution image based on median, mean, Lucy-Richardson, and Wiener filters. )is preprocessing stage is used to overcome the degradation present in the reference low-resolution image, which is a suitable kernel for producing the initial high-resolution image to be used in the reconstruction phase of the final image. then, L2 norm is employed for the data-fidelity term to minimize the residual among the predicted high-resolution image and the observed low-resolution images. Finally, bilateral total variation prior model is utilized to restrict the minimization function to a stable state of the generated HR image. )e experimental results of the synthetic data indicate that the proposed approaches have enhanced efficiency visually and quantitatively compared to other existing approaches

Enhanced MPR selection strategy for multicast OLSR

Wireless community networks (WCNs) are considered another form of ownership of internet protocol (IP) networks, where community members manage and own every piece of equipment in a decentralized way, and routing for traffic is done in a cooperative manner. However, the current routing protocols for WCNs suffer from stability and scalability issues. In this paper, an enhanced routing protocol is proposed based on the optimized link state routing (OLSR) protocol to meet the standards of efficiency in terms of stability and scalability. The proposed routing protocol is enhanced through two phases: multicasting expansion and multipoint relay (MPR) selection based on an analytical hierarchical process (AHP). The experimental results demonstrate that the proposed routing protocol outperforms the OLSR protocol in terms of network control overhead and packet delivery ratio by 18% and 1% respectively