DETECT AND ISOLATE THE LINEAR COMPOSITIONS IN SATELLITE IMAGES
Abstract views: 30 / PDF downloads: 18
Keywords:edge enhancement, nonlinear filter, dialation, erosion, remote sensing
Remote sensing data is a source for deriving a spatial graph of the Earth's surface, which is mainly composed of linear faults, drainage systems, road networks, and other natural and artificial landscapes. Their appearance clearly and accurately often requires algorithms and image processing methods to detect edges. On this basis, the subject of the research included identifying and automatically isolating the spatial characteristics of the earth's surface, such as linearity, drainage systems, and the boundaries of the earth's coverings. Robert and Sobel filters were used for the purpose of edge enhancement. . In order to isolate the edges clearly from the rest of the image contents, the adaptive obfuscation method was used in order to obtain a binary image that can be used in post-processing operations. For the purpose of isolating the edges better and closer to their true shape, a new algorithm was corrected to join and slim the edges, and this algorithm included the processes of extension and stripping. The final algorithm has been applied to different scenes from Nineveh Governorate captured by satellite sensors and aerial photography, and the results have proven reasonable success in detecting linear structures.
Kombe.T, Tonye.E, AssakoAssako.R.J," Neighborhood Treatments for Urban Network Extraction: Application to an RSO image of Douala (Cameroon)", IEEE Sitis 2005, pp 47-52.
A.F. Abdelnour, “Design Using Gröbner Bases,” Ph.D. dissertation, Polytechnic Univ., Brooklyn, New York, 2003.
M. Hema latha, S. Varadarajan, “Low resolution satellite Images contrast Enhancement Using Regularized-Histogram Equalization and DCT, ” IJERECE., 4, pp.109-113, 2017.
J. S. Blundell and D. W. Opitz, Object Recognition and Feature Extraction from Imagery: the Feature Analyst Approach, Visual Learning Systems, Missoula, Mont, USA, 2006.
D. Chaudhuri, N. K. Kushwaha, and A. Samal, “Semi-automated road detection from high resolution satellite images by directional morphological enhancement and segmentation techniques,” IEEE Journal of Applied Earth Observations and Remote Sensing, vol. 5, no. 5, pp. 1538–1544, 2012.
Pujare1,. Ankita, "Hardware Implementation of Sobel Edge Detection Algorithm", ICACC-2020.
Elliott, K. (2019). Sobel Algorithm. [image] Available at: http://blog.saush.com/2011/04/20/edgedetection-with-the-sobel-operator-in-ruby.
Rao .,Divyanshu, Rai. , Sapna, "A Review on Edge Detection Technique in Image Processing Techniques" , JSRSET | Vol. 2 , Issue 6, 2016.
Vladimir S. Ostojić, Đorđe S. Starčević," Thresholding Approach to Radiography ImageProcessing Acceleration", Telfor Journal, Vol. 9, No. 1, 2017.
Priyanka," Image Restoration of Image with Gaussian Filter", International Research Journal of Engineering and Technology, Vol. 07 Issue: 12 , Dec 2020.
Sunil Bhutada, Nakerakanti Yashwanth ,"Opening and closing in morphological image processing",World Journal of Advanced Research and Reviews, 2022.
N. J, M. S. S, and D. Pradeep, “A Fully Automatic Approach for Enhancement of Microarray Images,” J. Autom. Control Eng., vol. 1, no. 4, pp. 285–289, 2013.
Kaiqiang Zhang, a, Qiang Liao*"FPGA implementation of eight-direction Sobel edge detection algorithm based on adaptive threshold", IOP Publishing, journal of Physics ,2020.
How to Cite
Copyright (c) 2022 ARCENG (INTERNATIONAL JOURNAL OF ARCHITECTURE AND ENGINEERING) ISSN: 2822-6895
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.