scholarly journals Algorithm Selection for Edge Detection in Satellite Images by Neutrosophic WASPAS Method

2020 ◽  
Vol 12 (2) ◽  
pp. 548 ◽  
Author(s):  
Romualdas Bausys ◽  
Giruta Kazakeviciute-Januskeviciene ◽  
Fausto Cavallaro ◽  
Ana Usovaite
Keyword(s):  
Edge Detection ◽  
Satellite Images ◽  
Satellite Image ◽  
Visual Features ◽  
Algorithm Selection ◽  
Adaptive Selection ◽  
Detection Algorithms ◽  
Product Assessment ◽  
Areas Of Interest ◽  
Selection Of

Nowadays, integrated land management is generally governed by the principles of sustainability. Land use management usually is grounded in satellite image information. The detection and monitoring of areas of interest in satellite images is a difficult task. We propose a new methodology for the adaptive selection of edge detection algorithms using visual features of satellite images and the multi-criteria decision-making (MCDM) method. It is not trivial to select the most appropriate method for the chosen satellite images as there is no proper algorithm for all cases as it depends on many factors, like acquisition and content of the raster images, visual features of real-world images, and humans’ visual perception. The edge detection algorithms were ranked according to their suitability for the appropriate satellite images using the neutrosophic weighted aggregated sum product assessment (WASPAS) method. The results obtained using the created methodology were verified with results acquired in an alternative way—using the edge detection algorithms for specific images. This methodology facilitates the selection of a proper edge detector for the chosen image content.

scholarly journals Fractional Order Processing of Satellite Images

2021 ◽  
Vol 11 (11) ◽  
pp. 5288
Author(s):  
Manuel Henriques ◽  
Duarte Valério ◽  
Rui Melicio
Keyword(s):  
Edge Detection ◽  
Fractional Order ◽  
High Performance ◽  
Satellite Images ◽  
Automatic Detection ◽  
Automatic Processing ◽  
Order Processing ◽  
Detection Algorithms ◽  
Grey Scale ◽  
Fixed Set

Nowadays, satellite images are used in many applications, and their automatic processing is vital. Conventional integer grey-scale edge detection algorithms are often used for this. This study shows that the use of color-based, fractional order edge detection may enhance the results obtained using conventional techniques in satellite images. It also shows that it is possible to find a fixed set of parameters, allowing automatic detection while maintaining high performance.

scholarly journals Image Processing Techniques for Analysis of Satellite Images for Historical Maps Classification—An Overview

2020 ◽  
Vol 10 (12) ◽  
pp. 4207 ◽  
Author(s):  
Anju Asokan ◽  
J. Anitha ◽  
Monica Ciobanu ◽  
Andrei Gabor ◽  
Antoanela Naaji ◽  
...  
Keyword(s):  
Image Processing ◽  
Satellite Images ◽  
Satellite Image ◽  
Historical Maps ◽  
Satellite Imaging ◽  
Image Processing Techniques ◽  
Innovative Solutions ◽  
Satellite Image Processing ◽  
Processing Techniques ◽  
Selection Of

Historical maps classification has become an important application in today’s scenario of everchanging land boundaries. Historical map changes include the change in boundaries of cities/states, vegetation regions, water bodies and so forth. Change detection in these regions are mainly carried out via satellite images. Hence, an extensive knowledge on satellite image processing is necessary for historical map classification applications. An exhaustive analysis on the merits and demerits of many satellite image processing methods are discussed in this paper. Though several computational methods are available, different methods perform differently for the various satellite image processing applications. Wrong selection of methods will lead to inferior results for a specific application. This work highlights the methods and the suitable satellite imaging methods associated with these applications. Several comparative analyses are also performed in this work to show the suitability of several methods. This work will help support the selection of innovative solutions for the different problems associated with satellite image processing applications.

scholarly journals COMPARATIVE ESTIMATION OF EDGE DETECTION ALGORITHMS ON EARTH SATELLITE IMAGES

2019 ◽  
Vol 1 (1) ◽  
pp. 150-158
Author(s):  
Baliar V.B. ◽  
◽  
Malashkin R.M. ◽  
Mazurkiewicz O.F.
Keyword(s):  
Edge Detection ◽  
Satellite Images ◽  
Earth Satellite ◽  
Detection Algorithms

Distributed Approach to Process Satellite Image Edge Detection on Hadoop Using Artificial Bee Colony

2020 ◽  
Vol 11 (2) ◽  
pp. 80-94
Author(s):  
Tapan Sharma ◽  
Vinod Shokeen ◽  
Sunil Mathur
Keyword(s):  
Edge Detection ◽  
Artificial Bee Colony ◽  
Satellite Image ◽  
Detection Algorithms ◽  
Distributed Approach ◽  
Bee Colony ◽  
Image Edge Detection ◽  
Nature Inspired Algorithm ◽  
Canny Edge ◽  
Image Edge

The remote sensing domain has witnessed tremendous growth in the past decade, due to advancement in technology. In order to store and process such a large amount of data, a platform like Hadoop is leveraged. This article proposes a MapReduce (MR) approach to perform edge detection of satellite images using a nature-inspired algorithm Artificial Bee Colony (ABC). Edge detection is one of the significant steps in the field of image processing and is being used for object detection in the image. The article also compares two edge detection approaches on Hadoop with respect to scalability parameters such as scaleup and speedup. The experiment makes use of Amazon AWS Elastic MapReduce cluster to run MR jobs. It focuses on traditional edge detection algorithms like Canny Edge (CE) and the proposed MR based Artificial Bee Colony approach. It observes that for five images, the scaleup value of CE is 1.1 whereas, for MR-ABC, it is 1.2. Similarly, speedup values come out to be 1.02 and 1.04, respectively. The algorithm proposed by authors in this article scales comparatively better when compared to Canny Edge.

Selection and Preparation of Specific Tissue Regions For Tem Using Large Epoxy-Embedded Blocks

1973 ◽  
Vol 31 ◽  
pp. 324-325 ◽  
Author(s):  
P. M. Lowrie ◽  
W. S. Tyler
Keyword(s):  
Electron Microscopy ◽  
Anatomical Structures ◽  
Ultrastructural Studies ◽  
Transmission Electron ◽  
Microscopic Evaluation ◽  
Embedded Blocks ◽  
Specific Tissue ◽  
Definition Of ◽  
Areas Of Interest ◽  
Selection Of

The importance of examining stained 1 to 2μ plastic sections by light microscopy has long been recognized, both for increased definition of many histologic features and for selection of specimen samples to be used in ultrastructural studies. Selection of specimens with specific orien ation relative to anatomical structures becomes of critical importance in ultrastructural investigations of organs such as the lung. The uantity of blocks necessary to locate special areas of interest by random sampling is large, however, and the method is lacking in precision. Several methods have been described for selection of specific areas for electron microscopy using light microscopic evaluation of paraffin, epoxy-infiltrated, or epoxy-embedded large blocks from which thick sections were cut. Selected areas from these thick sections were subsequently removed and re-embedded or attached to blank precasted blocks and resectioned for transmission electron microscopy (TEM).

Adaptive Selection of Sampling Interval in Frequency Domain for Estimating the Poles of Scatterers

PIERS Online ◽  
2007 ◽  
Vol 3 (1) ◽  
pp. 106-110
Author(s):  
Shaogang Wang ◽  
Xinpu Guan ◽  
Dangwei Wang ◽  
Xingyi Ma ◽  
Yi Su
Keyword(s):  
Frequency Domain ◽  
Sampling Interval ◽  
Adaptive Selection ◽  
Selection Of
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