scholarly journals Image Compression Using Fractal Functions

2021 ◽  
Vol 5 (2) ◽  
pp. 31
Author(s):  
Olga Svynchuk ◽  
Oleg Barabash ◽  
Joanna Nikodem ◽  
Roman Kochan ◽  
Oleksandr Laptiev
Keyword(s):  
Image Compression ◽  
Spatial Data ◽  
Information Technologies ◽  
Radio Channel ◽  
Continuous Functions ◽  
Interesting Property ◽  
Geographic Information ◽  
Fractal Image Compression ◽  
Image Encoding ◽  
Fractal Functions

The rapid growth of geographic information technologies in the field of processing and analysis of spatial data has led to a significant increase in the role of geographic information systems in various fields of human activity. However, solving complex problems requires the use of large amounts of spatial data, efficient storage of data on on-board recording media and their transmission via communication channels. This leads to the need to create new effective methods of compression and data transmission of remote sensing of the Earth. The possibility of using fractal functions for image processing, which were transmitted via the satellite radio channel of a spacecraft, is considered. The information obtained by such a system is presented in the form of aerospace images that need to be processed and analyzed in order to obtain information about the objects that are displayed. An algorithm for constructing image encoding–decoding using a class of continuous functions that depend on a finite set of parameters and have fractal properties is investigated. The mathematical model used in fractal image compression is called a system of iterative functions. The encoding process is time consuming because it performs a large number of transformations and mathematical calculations. However, due to this, a high degree of image compression is achieved. This class of functions has an interesting property—knowing the initial sets of numbers, we can easily calculate the value of the function, but when the values of the function are known, it is very difficult to return the initial set of values, because there are a huge number of such combinations. Therefore, in order to de-encode the image, it is necessary to know fractal codes that will help to restore the raster image.

Supporting Aeronautical Information Management (AIM) Through Geographic Information Technologies and Spatial Data Infrastructures (SDI)

2016 ◽  
Vol 7 (3) ◽  
pp. 1-37
Author(s):  
Willington Siabato ◽  
Javier Moya-Honduvilla ◽  
Miguel Ángel Bernabé-Poveda
Keyword(s):  
Information Management ◽  
Spatial Data ◽  
Information Technologies ◽  
Geographic Information ◽  
Information Services ◽  
Air Traffic ◽  
Geographic Information Technologies ◽  
Web Architecture ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures

The way aeronautical information is managed and disseminated must be modernized. Current aeronautical information services (AIS) methods for storing, publishing, disseminating, querying, and updating the volume of data required for the effective management of air traffic control have become obsolete. This does not contribute to preventing airspace congestion, which turns into a limiting factor for economic growth and generates negative effects on the environment. Owing to this, some work plans for improving AIS and air traffic flow focus on data and services interoperability to allow an efficient and coordinated use and exchange of aeronautical information. Geographic information technologies (GIT) and spatial data infrastructures (SDI) are comprehensive technologies upon which any service that integrates geospatial information can rely. The authors are working on the assumption that the foundations and underlying technologies of GIT and SDI can be applied to support aeronautical data and services, considering that aeronautical information contains a large number of geospatial components. This article presents the design, development, and implementation of a Web-based system architecture to evolve and enhance the use and management of aeronautical information in any context, e.g., in aeronautical charts on board, in control towers, and in aeronautical information services. After conducting a study into the use of aeronautical information, it was found that users demand specific requirements regarding reliability, flexibility, customization, integration, standardization, and cost reduction. These issues are not being addressed with existing systems and methods. A system compliant with geographic standards (OGC, ISO) and aeronautical regulations (ICAO, EUROCONTROL) and supported by a scalable and distributed Web architecture is proposed. This proposal would solve the shortcomings identified in the study and provide aeronautical information management (AIM) with new methods and strategies. In order to seek aeronautical data and services interoperability, a comprehensive aeronautical metadata profile has been defined. This proposal facilitates the use, retrieval, updating, querying, and editing of aeronautical information, as well as its exchange between different private and public institutions. The tests and validations have shown that the proposal is achievable.

Efficient Domain Search for Fractal Image Compression Using Feature Extraction Technique

2012 ◽  
Vol 488-489 ◽  
pp. 1587-1591
Author(s):  
Amol G. Baviskar ◽  
S. S. Pawale
Keyword(s):  
Feature Extraction ◽  
Image Compression ◽  
Low Complexity ◽  
Contractive Mapping ◽  
Fractal Image Compression ◽  
Compression Technique ◽  
Image Encoding ◽  
Fractal Image ◽  
Coding Method ◽  
The Given

Fractal image compression is a lossy compression technique developed in the early 1990s. It makes use of the local self-similarity property existing in an image and finds a contractive mapping affine transformation (fractal transform) T, such that the fixed point of T is close to the given image in a suitable metric. It has generated much interest due to its promise of high compression ratios with good decompression quality. Image encoding based on fractal block-coding method relies on assumption that image redundancy can be efficiently exploited through block-self transformability. It has shown promise in producing high fidelity, resolution independent images. The low complexity of decoding process also suggested use in real time applications. The high encoding time, in combination with patents on technology have unfortunately discouraged results. In this paper, we have proposed efficient domain search technique using feature extraction for the encoding of fractal image which reduces encoding-decoding time and proposed technique improves quality of compressed image.

THE PARALLEL-PIPELINED IMPLEMENTATION OF THE FRACTAL IMAGE COMPRESSION FOR RECONFIGURABLE COMPUTING SYSTEMS

2021 ◽  
pp. 37-44
Author(s):  
I. I. Levin ◽  
M. D. Chekina
Keyword(s):  
Image Compression ◽  
Reconfigurable Computing ◽  
Fractal Image Compression ◽  
Computing Systems ◽  
Image Encoding ◽  
Fractal Image ◽  
Computational Structure ◽  
Parallel Pipeline ◽  
Performance Reduction ◽  
Critical Resource

The developed fractal image compression method, implemented for reconfigurable computing systems is described. The main idea parallel fractal image compression based on parallel execution pairwise comparison of domain and rank blocks. Achievement high performance occurs at the expense of simultaneously comparing maximum number of pairs. Implementation fractal image compression for reconfigurable computing systems has two critical resources, as number of input channels and FPGA Look-up Table (LUT). The main critical resource for fractal image compression is data channels, and implementation this task for reconfigurable computing systems requires parallel-pipeline computations organization replace parallel, preliminarily produced performance reduction parallel computational structure. The main critical resource for fractal image compression is data channels, and implementation this task for reconfigurable computing systems requires parallel-pipeline computations organization replace parallel computations organiation. For using parallel-pipeline computations organization, preliminarily have produce performance reduction parallel computational structure. Each operator has routed to computational structure sequentially (bit by bit) to save computational resources and reduces equipment downtime. Storing iterated functions system coefficients for image encoding has been introduced in data structure, which correlates between corresponding parameters the numbers of rank and domain blocks. Applying this approach for parallel-pipeline programs allows scaling computing structure to plurality programmable logic arrays (FPGAs). Task implementation on the reconfigurable computer system Tertius-2 containing eight FPGAs 15 000 times provides performed acceleration relatively with universal multi-core processor, and 18 – 25 times whit to existing solutions for FPGAs.

Supporting Aeronautical Information Management (AIM) Through Geographic Information Technologies and Spatial Data Infrastructures (SDI)

2019 ◽  
pp. 306-348
Author(s):  
Willington Siabato ◽  
Javier Moya-Honduvilla ◽  
Miguel Ángel Bernabé-Poveda
Keyword(s):  
Information Management ◽  
Spatial Data ◽  
Information Technologies ◽  
Geographic Information ◽  
Information Services ◽  
Air Traffic ◽  
Geospatial Information ◽  
Geographic Information Technologies ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures

The way aeronautical information is managed and disseminated must be modernized. Current aeronautical information services (AIS) methods for storing, publishing, disseminating, querying, and updating the volume of data required for the effective management of air traffic control have become obsolete. This does not contribute to preventing airspace congestion, which turns into a limiting factor for economic growth and generates negative effects on the environment. Owing to this, some work plans for improving AIS and air traffic flow focus on data and services interoperability to allow an efficient and coordinated use and exchange of aeronautical information. Geographic information technologies (GIT) and spatial data infrastructures (SDI) are comprehensive technologies upon which any service that integrates geospatial information can rely. The authors are working on the assumption that the foundations and underlying technologies of GIT and SDI can be applied to support aeronautical data and services, considering that aeronautical information contains a large number of geospatial components. This article presents the design, development, and implementation of a Web-based system architecture to evolve and enhance the use and management of aeronautical information in any context, e.g., in aeronautical charts on board, in control towers, and in aeronautical information services. After conducting a study into the use of aeronautical information, it was found that users demand specific requirements regarding reliability, flexibility, customization, integration, standardization, and cost reduction. These issues are not being addressed with existing systems and methods. A system compliant with geographic standards (OGC, ISO) and aeronautical regulations (ICAO, EUROCONTROL) and supported by a scalable and distributed Web architecture is proposed. This proposal would solve the shortcomings identified in the study and provide aeronautical information management (AIM) with new methods and strategies. In order to seek aeronautical data and services interoperability, a comprehensive aeronautical metadata profile has been defined. This proposal facilitates the use, retrieval, updating, querying, and editing of aeronautical information, as well as its exchange between different private and public institutions. The tests and validations have shown that the proposal is achievable.

scholarly journals THE ROLE OF GEOMATICS ENGINEER IN SMART CITIES: A VIEW WITHIN THE FRAMEWORK OF TURKISH 2020–2023 NATIONAL SMART CITIES STRATEGY AND ACTION PLAN

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 333-341
Author(s):  
K. Konur ◽  
R. M. Alkan
Keyword(s):  
Spatial Data ◽  
Information Technologies ◽  
Smart Cities ◽  
Action Plan ◽  
Geographic Information ◽  
Geographic Information Technologies ◽  
Geographic Data ◽  
Technological Developments ◽  
Made In

Abstract. The development of technology resulted major revolutions in the cities. With the integration of technological developments into cities, the concept of smart cities began to emerge. Today, applications are made on smart cities in many countries. It is not possible to build a smart city without geographic data. It is one of the main duties of Geomatics Engineers to produce, use, process and finalize the geographic data and present it to the user. In this study, referring to the role of Geomatics Engineer in smart cities across Turkey 2020-2023 National Smart Cities Strategy and Action Plan framework is made in the investigations. When this plan is examined, it is seen that the importance of geographical/geo-spatial data and geo-information technologies for the realization of smart cities is an undeniable fact. In the 2020–2023 National Smart Cities Strategy and Action Plan, it has been clearly demonstrated that Geographic Information Systems and Geographic Information Technologies have a great role in creating smart cities.

scholarly journals BiGeo: A Foundational PaaS Framework for Efficient Storage, Visualization, Management, Analysis, Service, and Migration of Geospatial Big Data—A Case Study of Sichuan Province, China

2019 ◽  
Vol 8 (10) ◽  
pp. 449
Author(s):  
Xi Liu ◽  
Lina Hao ◽  
Wunian Yang
Keyword(s):  
Big Data ◽  
Spatial Data ◽  
Information Technologies ◽  
Earth Science ◽  
Rapid Development ◽  
Geographic Information ◽  
Sichuan Province ◽  
Geographic Information Technologies ◽  
Information Research ◽  
Big Data Technologies

With the rapid development of big data, numerous industries have turned their focus from information research and construction to big data technologies. Earth science and geographic information systems industries are highly information-intensive, and thus there is an urgent need to study and integrate big data technologies to improve their level of information. However, there is a large gap between existing big data and traditional geographic information technologies. Owing to certain characteristics, it is difficult to quickly and easily apply big data to geographic information technologies. Through the research, development, and application practices achieved in recent years, we have gradually developed a common geospatial big data solution. Based on the formation of a set of geospatial big data frameworks, a complete geospatial big data platform system called BiGeo was developed. Through the management and analysis of massive amounts of spatial data from Sichuan Province, China, the basic framework of this platform can be better utilized to meet our needs. This paper summarizes the design, implementation, and experimental experience of BiGeo, which provides a new type of solution to the research and construction of geospatial big data.

scholarly journals Analysis and Assessment of Lithuanian Road Accidents by AHP Method

2018 ◽  
Vol 13 (3) ◽  
Author(s):  
Marius Jakimavičius
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Analytical Hierarchy Process ◽  
Spatial Data ◽  
Hot Spots ◽  
Information Technologies ◽  
Geographic Information ◽  
Road Accidents ◽  
Hierarchy Process ◽  
Process Method

Lithuanian road accidents were evaluated based on the geographic information systems and multi-criteria method of Analytical Hierarchy Process This paper presents the methodology for selecting and ranking high accident concentration sections on the roads of national significance. Methodology involves the following process phases: 1) preparation of spatial data of the road accidents; 2) estimation of road sections with a high accident rate; 3) calculation of spatial statistics for estimation of accident points and hot spots; 4) selecting indicators for multi-criteria assessment; 5) calculation by Analytical Hierarchy Process method and ranking the selected high accident concentration sections. Assessment of spatial clustering of accidents and hot spots was carried out following geo-information technologies and using Getis-Ord Gi  statistics and point density functions. This geospatial criterion was integrated into multicriteria assessment for ranking the high accident concentration sections by using the Analytical Hierarchy Process method. Presented method is useful for various agencies in order to improve their planning and management strategies for better traffic conditions as well as to reduce the number of accidents. The result of the research presents selection methodology of dangerous accident section and ranking of the tenth the most dangerous sections involving geographic information systems and Analytical Hierarchy Process method.

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