A COMPARATIVE STUDY OF FEW SATELLITE IMAGE CLUSTERING METHODS BASED ON SPATIAL NEIGHBORHOOD INFORMATION

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.

FATEMI S.B.; MOBASHERI M.R.; ABKAR A.A.

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

Journal Paper

Paper Information

Journal: JOURNAL OF GEOMATICS SCIENCE AND TECHNOLOGY Year:2014 | Volume:3 | Issue:4 Page(s): 77-89

Download Full-Text

Persian Verion

View:

890

Download:

Cites:

Information Journal Paper

Title

A COMPARATIVE STUDY OF FEW SATELLITE IMAGE CLUSTERING METHODS BASED ON SPATIAL NEIGHBORHOOD INFORMATION

Author(s)

FATEMI S.B. | MOBASHERI M.R. | ABKAR A.A. | Issue Writer Certificate

Keywords

CLUSTERINGQ2

REMOTE SENSINGQ2

SATELLITE IMAGEQ2

SPATIAL CONTEXTQ1

Abstract

In order to enhance the accuracy of the image CLUSTERING, many CLUSTERING algorithms such as semi-supervised CLUSTERING, CLUSTERING ensembles and CoCLUSTERING have so far been proposed where the most effective strategy is when SPATIAL CONTEXT in CLUSTERING is considered. In this study, four CLUSTERING methods in which the spatial neighborhood information is used are investigated. These include: using texture information, object based CLUSTERING, Markov random field CLUSTERING and applying majority filter on the CLUSTERING results. These four methods are tested on the two synthetic and two real high resolution SATELLITE IMAGEs. The results show that using texture information in CLUSTERING can enhance the overall accuracy of the CLUSTERING of the real images up to 10.8% relative to the simplek-means CLUSTERING. Markov random field CLUSTERING of the synthetic images shows 22.8% improvement in overall accuracy. The results show that using SPATIAL CONTEXT can enhance the overall accuracy of the SATELLITE IMAGE CLUSTERING.

Cites

No record.

References

No record.

Cite

APA: Copy

FATEMI, S.B., MOBASHERI, M.R., & ABKAR, A.A.. (2014). A COMPARATIVE STUDY OF FEW SATELLITE IMAGE CLUSTERING METHODS BASED ON SPATIAL NEIGHBORHOOD INFORMATION. JOURNAL OF GEOMATICS SCIENCE AND TECHNOLOGY, 3(4), 77-89. SID. https://sid.ir/paper/249535/en

Vancouver: Copy

FATEMI S.B., MOBASHERI M.R., ABKAR A.A.. A COMPARATIVE STUDY OF FEW SATELLITE IMAGE CLUSTERING METHODS BASED ON SPATIAL NEIGHBORHOOD INFORMATION. JOURNAL OF GEOMATICS SCIENCE AND TECHNOLOGY[Internet]. 2014;3(4):77-89. Available from: https://sid.ir/paper/249535/en

IEEE: Copy

S.B. FATEMI, M.R. MOBASHERI, and A.A. ABKAR, “A COMPARATIVE STUDY OF FEW SATELLITE IMAGE CLUSTERING METHODS BASED ON SPATIAL NEIGHBORHOOD INFORMATION,” JOURNAL OF GEOMATICS SCIENCE AND TECHNOLOGY, vol. 3, no. 4, pp. 77–89, 2014, [Online]. Available: https://sid.ir/paper/249535/en

Related Journal Papers