Method for Assessing the Sustainability of the Information Direction, Functioning on the Resources of the Communication Network with Failures

The article presents the main directions of the qualitative and quantitative assessment of sustainability in the field of infocommunications, shows the differences in approaches to the definition of sustainability. A method is proposed that differs from the known well-grounded application of the provisions of the theory of random impulse flows. The generalized impulse flow describes the robustness of data transmission in the information direction. The estimation method allows one to take into account both the states of the elements of a composite channel, represented by impulse flows of failures and restorations, and transient processes and sub-processes of information exchange (transmission over a communication line, switching, storage in memory, destructive influences, etc.), represented by separate impulse streams. The variability of the composition of the impulse streams makes it possible to increase the accuracy and reliability of the assessment.

An Accession for Image Denoising by Multiple Filter and Correlative Examination for Random Impulse Noise

Denoising an image is a significant problem in the processing of digital images. Any impulse noise damages the image and the aim of denoising is to remove noise and restore the high-quality image as much as possible. This paper aims to develop a method to discriminate between corrupted and uncorrupted pixels and develop a novel filter to denoise the image. It is also necessary to consider images with different level of noise of various applications to develop an optimal system to remove the noise for further processing. In this paper different filtering techniques such as Median-Filter (MF), Weighted -Median-Filter (WMF),Centre-Weighted Median filter (CWMF), and adaptive centre weighted median filter (ACWMF) are used for denoising, also a novel filter Asymmetric Trimmed Median Filter(ATMF) is designed which outperforms compared to the filters designed earlier. Experimentation is carried by considering the dataset size of 700 noisy images. The average PSNR value of proposed system is 28.12%(DB).