In many applications, Image de-noising and improvement represent essential processes in presence of colored noise such that in underwater. Power spectral density of the noise is changeable within a definite frequency range, and autocorrelation noise function is does not like delta function. So, noise in underwater is characterized as colored noise. In this paper, a novel image de-noising method is proposed using multi-level noise power estimation in discrete wavelet transform with different basis functions. Peak signal to noise ratio (PSNR) and mean squared error represented performance measures that the results of this study depend on it. The results of various bases of wavelet such as: Daubechies (db), biorthogonal (bior.) and symlet (sym.), show that denoising process that uses in this method produces extra prominent images and improved values of PSNR than other methods.
<p>A detailed survey on the process of data collection from multiple sources in Wireless Sensor Networks (WSNs) is introduced. The topologies that determine the location of the network components with respect to each other are presented. These topologies are often referred to as Mobility topologies. The performance of the overall WSN architecture significantly depends on these topologies. As a consequence, these topologies are elaborately compared and discussed. The most common network components that efficiently collaborate in data collection process are explained. To highlight the data collection process as a subject of our concern, the phases that describe the stages of the data collection are illustrated. These phases consist of three successive stages: discovery, data transfer, and routing. To sum up, the most recent approaches for developing the process of data collection in multiple-source WSNs are also presented.</p>
The mode group diversity multiplexing (MGDM) multicast technology uses optical multiple input and output (O-MIMO) technology to provide greater capacity and the ability to transmit information over multi-mode fiber (MMF). The MGDM system has a benefit in terms of capacity expansion, which led to interest in its use in most optical communications. The MGDM exploits the optical fiber bandwidth by inserting spatial light detection, which increases the capacity of the MMF. This research aims to study the optical systems used for the MGDM technology, and to identify the methods of their analysis and design of O-MIMO systems to increase the amplitude of this signal. The conditions of light entry into the optical fiber such as typical spot size, radial displacements, angle, wavelength, and radius of the detectors sections are improved. Numerical MATLAB simulation is used to improve the amplitude of graded index multimode fiber (GI-MMF) and compared to the existing aggregation systems. Moreover, this method was simulated to improve the input and detection conditions to increase the O-MIMO capacity using the MGDM technique. Finally, the capacity of the MGDM system was studied and compared with different channels, and it is noticed that the capacity of the system increases with increasing the number of channels.
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