AUTOMATIC DETECTION OF LINEATION IN SATELLITE IMAGES AND AERIAL PHOTOS USING RADON TRANSFORM

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

KARIMPOULI SADEGH; ABBASIZADEH SAEED; AMINI EGHBAL

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF MINING ENGINEERING (IRJME) Year:2016 | Volume:10 | Issue:29 Page(s): 41-49

Download Full-Text

Persian Verion

View:

1,896

Download:

Cites:

Information Journal Paper

Title

AUTOMATIC DETECTION OF LINEATION IN SATELLITE IMAGES AND AERIAL PHOTOS USING RADON TRANSFORM

Author(s)

KARIMPOULI SADEGH | ABBASIZADEH SAEED | AMINI EGHBAL | Issue Writer Certificate

Keywords

LINEATIONQ2

AERIAL PHOTOQ2

SATELLITE IMAGEQ2

GAUSSIAN DERIVATIVEQ2

RADON TRANSFORMQ2

Abstract

In each area, knowledge of linear structures consist of faults and fractures is useful for geological and hydrogeological studies and for exploration of mineral resources. LINEATION map is usually extracted from spatial data such as SATELLITE IMAGEs and AERIAL PHOTOs. Although visual extracting is the popular method, user errors are highly reduced by automatic extraction methods. The best methods are the ones who combine edge enhancement filters and feature extraction algorithms. In this study, an algorithm is presented based on Gaussian kernel derivative operator as an edge enhancer and RADON TRANSFORM as the linear shape extractor in a gridded image. This method was tested on a simple image with high level of noises which produced promising results. This was also implemented on a Landsat image (TM) from a sandstone plateau in northern state of Australia, an arial photo from southern Nevada and a manual photo from Mozaeic Canyon, California and its results compared with another method on the same database. Results show that this algorithm is lonely effective enough to detect LINEATION. These results, even with a very simple algorithm with low computation cost, are highly comparative with the results of a complicated method. It should be mentioned that this method produces discontinued results for continues LINEATION, but it is able to capture non-linear structures.

Cites

No record.

References

No record.

Cite

APA: Copy

KARIMPOULI, SADEGH, ABBASIZADEH, SAEED, & AMINI, EGHBAL. (2016). AUTOMATIC DETECTION OF LINEATION IN SATELLITE IMAGES AND AERIAL PHOTOS USING RADON TRANSFORM. IRANIAN JOURNAL OF MINING ENGINEERING (IRJME), 10(29), 41-49. SID. https://sid.ir/paper/117089/en

Vancouver: Copy

KARIMPOULI SADEGH, ABBASIZADEH SAEED, AMINI EGHBAL. AUTOMATIC DETECTION OF LINEATION IN SATELLITE IMAGES AND AERIAL PHOTOS USING RADON TRANSFORM. IRANIAN JOURNAL OF MINING ENGINEERING (IRJME)[Internet]. 2016;10(29):41-49. Available from: https://sid.ir/paper/117089/en

IEEE: Copy

SADEGH KARIMPOULI, SAEED ABBASIZADEH, and EGHBAL AMINI, “AUTOMATIC DETECTION OF LINEATION IN SATELLITE IMAGES AND AERIAL PHOTOS USING RADON TRANSFORM,” IRANIAN JOURNAL OF MINING ENGINEERING (IRJME), vol. 10, no. 29, pp. 41–49, 2016, [Online]. Available: https://sid.ir/paper/117089/en

Related Journal Papers