[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 5, Issue 1 (6-2017) ::
jgit 2017, 5(1): 89-109 Back to browse issues page
Evaluation of SLIC superpixel and DBSCAN clustering algorithms in segmentation of ultra-high resolution remote sensing imagery over urban areas
Ahmad Hadavand * , Mohamad Saadatseresht , Saeed Homayouni , Zeinab Gharib Bafghi
University of Tehran
Abstract:   (4422 Views)

By increasing the spatial resolution of remote sensing imaging sensors, the image analyzing paradigm is
moving towards the object based image analysis approaches, instead of single pixels. Among the common
segmentation algorithms, super-pixel methods are presenting themselves as the new tools in computer vision.
In this paper, the capabilities of a state-of-the-art super-pixel algorithm, namely called SLIC, is investigated for
creating image segments from ultra-high resolution remote sensing images. In our proposed method, square
and hexagonal super-pixels were formed and then DBSCAN clustering algorithm is employed to build image
segments from these pixels. The results were compared to image segments obtained from FNEA algorithm, a
well-known method for remote sensing image segmentation. Visual and quantitative evaluations demonstrate
the efficiency of proposed method.

Keywords: Super-pixel, Segmentation, Ultra-high resolution Images, Remote Sensing.
Full-Text [PDF 3015 kb]   (2046 Downloads)    
Type of Study: Research | Subject: Aerial Photogrammetry
Received: 2017/06/10 | Accepted: 2017/06/10 | Published: 2017/06/10
Send email to the article author



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Hadavand A, Saadatseresht M, Homayouni S, Gharib Bafghi Z. Evaluation of SLIC superpixel and DBSCAN clustering algorithms in segmentation of ultra-high resolution remote sensing imagery over urban areas. jgit 2017; 5 (1) :89-109
URL: http://jgit.kntu.ac.ir/article-1-426-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 5, Issue 1 (6-2017) Back to browse issues page
نشریه علمی-پژوهشی مهندسی فناوری اطلاعات مکانی Engineering Journal of Geospatial Information Technology
Persian site map - English site map - Created in 0.04 seconds with 36 queries by YEKTAWEB 4652