(1987). Applied Probability and Queues. Journal of the Operational Research Society: Vol. 38, No. 11, pp. 1095-1096.

https://link.springer.com/content/pdf/10.1057%2Fjors.1987.184.pdf

Applied Probability and Queues

Adaptive vector median filtering

From the Publisher:
Image Processing Handbook covers methods for two different purposes:
Improving the visual appearance of images to a human viewerPreparing images for measurement of the features and structures present.

The handbook presents an extensive collection of image processing tools, enabling the user of computer-based system to understand those methods provided in packaged software and to program additions needed for particular applications. Comparisons are presented of different algorithms that may be used for similar purposes, including a selection of representative pictures from light and electron microscopes as well as macroscopic, satellite, and astronomical images.
Image Processing Handbook examines the rapid, powerful developments in graphic information, covering the array of concepts and techniques in high-end imaging software. With balanced, complete descriptions, the text outlines frequency space methods with extensive mathematical presentation and spatial domain processing. This handbook teaches by example -- by seeing what various operations do to representative images, the reader will discover how and why to use them. The text encourages the reader to use its information with a real source of images and a computer-based system as well as to freely experiment with different methods to determine the most appropriate for his or her particular needs.To facilitate the learning process, Reindeer Games in Charlotte, North Carolina, offers The Image Processing Tool Kit, a CD-ROM containing more than 150 images and more than 150 Photoshop-compatible plug-ins that implement the algorithms discussed. This revision of the established standard acts as a singular resource for professionals in the medical, biological, and materials sciences as well as a range of engineering venues, including electrical and computer engineering, optical engineering, telecommunications, and artificial intelligence.

Image Processing Handbook, Fourth Edition

Security, privacy & efficiency of sustainable Cloud Computing for Big Data & IoT

Wireless sensor networks are one of the most promising emerging technologies, providing the opportunity for real-time monitoring of geographical regions (remote and hostile) that are prone to disasters. With a focus on landslide detection, this work reaffirms the capability of wireless sensor networks for disaster mitigation. A complete functional system consisting of 50 geological sensors and 20 wireless sensor nodes was deployed in Idukki, a district in the southwestern region of Kerala State, India, a highly landslide prone area. The wireless sensor network system has, for the past three years, gathered vast amounts of data such as correlated sensor data values on rainfall, moisture, pore pressure and movement, along with other geological, hydrological and soil properties, helping to provide a better understanding of the landslide scenario. Using the wireless sensor networks, system was developed an innovative three level landslide warning system (Early, Intermediate and Imminent). This system has proven its validity by delivering a real warning to the local community during heavy rains in the July 2009 monsoon season. The implementation of this system uses novel data aggregation methods for power optimization in the field deployment. A report on unanticipated challenges that were faced in the field deployment of the wireless sensor networks and the novel solutions devised to overcome them are presented here.

Design, development, and deployment of a wireless sensor network for detection of landslides

In this paper, a novel approach to the impulsive noise removal in color images is presented. The proposed technique employs the switching scheme based on the impulse detection mechanism using the so-called peer group concept. Compared to the vector median filter and other commonly used multichannel filters, the proposed technique consistently yields very good results in suppressing both the random and fixed-valued impulsive noise. The main advantage of the proposed noise detection framework is its enormous computational speed, which enables efficient filtering of color images in real-time applications.

Fast detection and impulsive noise removal in color images

https://www.comm.utoronto.ca/~kostas/Publications2008/pub/32.pdf

Self-adaptive algorithm of impulsive noise reduction in color images

In this paper, we address the problem of impulsive noise reduction in multichannel images. A new class of filters for noise attenuation is introduced and its relationship with commonly used filtering techniques is investigated. The computational complexity of the new filter is lower than that of the vector median filter (VMF). Extensive simulation experiments indicate that the new filter outperforms the VMF, as well as other techniques currently used to eliminate impulsive noise in color images.

/pdf/fast-adaptive-similarity-based-impulsive-noise-reduction-32316vscds.pdf

Fast adaptive similarity based impulsive noise reduction filter

A new approach to the problem of impulsive-noise reduction for color images is introduced. The major advantage of the technique is that it filters out the noise component while adapting itself to the local image structures. In this way the algorithm is able to eliminate strong impulsive noise while preserving edges and fine image details. As the algorithm is a fuzzy modification of the commonly used vector median operator, it is very fast and easy to implement. Our results show that the proposed method outperforms all standard algorithms for the reduction of impulsive noise in color images. © 2001 Society of Photo-Optical Instrumenta- tion Engineers. (DOI: 10.1117/1.1367347)

/pdf/on-the-reduction-of-impulsive-noise-in-multichannel-image-29gv8ku6de.pdf

On the reduction of impulsive noise in multichannel image processing

Analysis of AQM queues with queue size based packet droppingQueueing systems in which an arriving job is blocked and lost with a probability that depends on the queue size are studied. The study is motivated by the popularity of Active Queue Management AQM algorithms proposed for packet queueing in Internet routers. AQM algorithms often exploit the idea of queue-size based packet dropping. The main results include analytical solutions for queue size distribution, loss ratio and throughput. The analytical results are illustrated via numerical examples that include some commonly used blocking probabilities dropping functions.

/pdf/analysis-of-aqm-queues-with-queue-size-based-packet-dropping-3dlsdvms8w.pdf

Andrzej Chydzinski

Papers

Fast detection and impulsive noise removal in color images

Self-adaptive algorithm of impulsive noise reduction in color images

Fast adaptive similarity based impulsive noise reduction filter

On the reduction of impulsive noise in multichannel image processing

Analysis of AQM queues with queue size based packet dropping