An adaptive noise removal approach for restoration of digital images corrupted by multimodal noise

Data smoothing algorithms are commonly applied to reduce the level of noise and eliminate the weak textures contained in digital images. Anisotropic diffusion algorithms form a distinct category of noise removal approaches that implement the smoothing process locally in agreement with image features such as edges that are typically determined by applying diverse partial differential equation (PDE) models. While this approach is opportune since it allows the implementation of feature-preserving data smoothing strategies, the inclusion of the PDE models in the formulation of the data smoothing process compromises the performance of the anisotropic diffusion schemes when applied to data corrupted by non-Gaussian and multimodal image noise. In this paper we first evaluate the positive aspects related to the inclusion of a multi-scale edge detector based on the generalisation of the Di Zenzo operator into the formulation of the anisotropic diffusion process. Then, we introduce a new approach that embeds the vector median filtering into the discrete implementation of the anisotropic diffusion in order to improve the performance of the noise removal algorithm when applied to multimodal noise suppression. To evaluate the performance of the proposed data smoothing strategy, a large number of experiments on various types of digital images corrupted by multimodal noise were conducted.Keywords — Anisotropic diffusion, vector median filtering, feature preservation, multimodal noise, noise removal

Automated real time detection of solar wind shocks and consequences for the identification of SSC and SI events

Algorithms have been developed to automatically detect Earth bound shocks in the solar wind as measured by the ACE satellite. These involve simple threshold techniques and wavelet analysis. One practical application of this shock detection is that it can provide power companies with advanced warning of the potential for geomagnetically induced currents. The automatically detected shocks have been tested against published lists of known shocks and accuracy statistics are presented. Another use for automated shock detection is an aid to the preparation of lists of rapid variations: SSC and SI events. To contribute to the IAGA published list of rapid variations, as prepared by Ebro Observatory, BGS staff routinely identify, scale and classify the events recorded at the three UK magnetic observatories. This is carried out using the criteria from the Atlas of Rapid Variations (1959) and subsequent IAGA instructions. The usefulness of automated detection of solar wind shocks for this task is examined by testing these against lists of identified SSC and SI events

Extraction of tidal channel networks from airborne scanning laser altimetry and aerial photography

The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea

Neighborhood coherence and edge based approaches to film scene extraction

In order to enable high-level semantics-based video annotation and interpretation, we tackle the problem of automatic decomposition of motion pictures into meaningful story units, namely scenes. Since a scene is a complicated and subjective concept, we first propose guidelines from film production to determine when a scene change occurs in film. We examine different rules and conventions followed as part of Film Grammar to guide and shape our algorithmic solution for determining a scene boundary. Two different techniques are proposed as new solutions in this paper. Our experimental results on 10 full-length movies show that our technique based on shot sequence coherence performs well and reasonably better than the color edges-based approach

МОДИФИКАЦИЯ СТАТИСТИЧЕСКОГО АЛГОРИТМА ВЫДЕЛЕНИЯ КОНТУРОВ

Целью данной работы было создание, реализация и сравнение модифицированного алгоритма выделения контура, который базируется на статистическом алгоритме, с классическим статистическим алгоритмом. В результате проведенной работы был модифицирован алгоритм, описаны основные особенности, проблемы и требования к данному семейству алгоритмов и особенности реализации самого алгоритма. Также написан программный код на языке программирования Java, при исполнении которого осуществляется выделение контуров на изображении двумя способами: классическим и модифицированным. Также были протестированы возможности, сложность, время выполения данных алгоритмов. Результаты данной работы могут быть использованы в любых системах распознавания образов. Также были рассмотрены недостатки подобных алгоритмов и сформированы цели для дальнейшего исследования этой темы.Метою даної роботи було створення, реалізація і порівняння модифікованого алгоритму виділення контуру, який базується на статистичному алгоритмі, з класичним статистичним алгоритмом. В результаті проведеної роботи був модифікований алгоритм, описані основні особливості, проблеми і вимоги до даного сімействі алгоритмів і особливості реалізації самого алгоритму. Також написаний програмний код на мові програмування Java, при виконанні якого здійснюється виділення контурів на зображенні двома способами: класичним і модифікованим. Протестовані можливості, складність, час виконання даних алгоритмів. Результати даної роботи можуть бути використані в будь-яких системах розпізнавання образів. Також були розглянуті недоліки подібних алгоритмів і сформовані цілі для подальшого дослідження цієї теми.The purposes of this work are to create, implement and compare a modified algorithm for contour detection which is based on a statisticalalgorithm with a classic statistic algorithm. As a result of the work, the algorithm was modified, described the main features of the problem, the requirements to contour detection algorithms and the problems of algorithm implementation. Also program code in the Java programming language is written, which detects contour on the image in two ways, classical and modified. Also was tested: features, complexity, time of execution of these algorithms. The results of this work can be used in any image recognition system. Also, the shortcomings of such algorithms were considered and goals for further researches of this topic were formed

An Extended Review on Fabric Defects and Its Detection Techniques

In Textile Industry, Quality of the Fabric is the main important factor. At the initial stage, it is very essential to identify and avoid the fabrics faults/defects and hence human perception consumes lot of time and cost to reveal the fabrics faults. Now-a-days Automated Inspection Systems are very useful to decrease the fault prediction time and gives best visualizing clarity- based on computer vision and image processing techniques. This paper made an extended review about the quality parameters in the fiber-to-fabric process, fabrics defects detection terminologies applied on major three clusters of fabric defects knitting, woven and sewing fabric defects. And this paper also explains about the statistical performance measures which are used to analyze the defect detection process. Also, comparison among the methods proposed in the field of fabric defect detection