A texture-based approach for extracting residential areas from high-resolution imagery

Gu Juan; Chen Jun; Zhang Hongwei; Zhouc Qiming

doi:10.1117/12.713248

A texture-based approach for extracting residential areas from high-resolution imagery

Gu Juan^*, Chen Jun, Zhang Hongwei, Zhouc Qiming

^*Corresponding author for this work

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

When spectral classification approach has lost its efficiency in object recognition from finer resolution imagery, texture plays more and more important role. This paper introduces an approach of using the combination of four kinds of texture measurements (grey mean value, standard deviation, edge point density, edge line density) to extracting residential areas from high-resolution imagery. The job of extraction is performed in three steps: (1) Extraction of candidate pixels of residential areas based on mean grey value and standard deviation; (2) Extraction of candidate areas of residential areas based on edge point density; (3) Verification of candidate areas of residential areas based on edge line density. An experiment by using IKONOS PAN image is given to verify the correct of the method.

Original language	English
Title of host publication	Geoinformatics 2006
Subtitle of host publication	Remotely Sensed Data and Information
DOIs	https://doi.org/10.1117/12.713248
Publication status	Published - 2006
Event	Geoinformatics 2006: Remotely Sensed Data and Information - Wuhan, China Duration: 28 Oct 2006 → 29 Oct 2006

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	6419
ISSN (Print)	0277-786X

Conference

Conference	Geoinformatics 2006: Remotely Sensed Data and Information
Country/Territory	China
City	Wuhan
Period	28/10/06 → 29/10/06

Scopus Subject Areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

User-Defined Keywords

Edge line density
Edge point density
Grey mean value
Residential areas
Stand deviation
Textures

Access to Document

10.1117/12.713248

Cite this

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title = "A texture-based approach for extracting residential areas from high-resolution imagery",

abstract = "When spectral classification approach has lost its efficiency in object recognition from finer resolution imagery, texture plays more and more important role. This paper introduces an approach of using the combination of four kinds of texture measurements (grey mean value, standard deviation, edge point density, edge line density) to extracting residential areas from high-resolution imagery. The job of extraction is performed in three steps: (1) Extraction of candidate pixels of residential areas based on mean grey value and standard deviation; (2) Extraction of candidate areas of residential areas based on edge point density; (3) Verification of candidate areas of residential areas based on edge line density. An experiment by using IKONOS PAN image is given to verify the correct of the method.",

keywords = "Edge line density, Edge point density, Grey mean value, Residential areas, Stand deviation, Textures",

author = "Gu Juan and Chen Jun and Zhang Hongwei and Zhouc Qiming",

year = "2006",

doi = "10.1117/12.713248",

language = "English",

isbn = "0819465283",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

booktitle = "Geoinformatics 2006",

}

Juan, G, Jun, C, Hongwei, Z & Qiming, Z 2006, A texture-based approach for extracting residential areas from high-resolution imagery. in Geoinformatics 2006: Remotely Sensed Data and Information., 64191H, Proceedings of SPIE - The International Society for Optical Engineering, vol. 6419, Geoinformatics 2006: Remotely Sensed Data and Information, Wuhan, China, 28/10/06. https://doi.org/10.1117/12.713248

A texture-based approach for extracting residential areas from high-resolution imagery. / Juan, Gu; Jun, Chen; Hongwei, Zhang et al.
Geoinformatics 2006: Remotely Sensed Data and Information. 2006. 64191H (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6419).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - A texture-based approach for extracting residential areas from high-resolution imagery

AU - Juan, Gu

AU - Jun, Chen

AU - Hongwei, Zhang

AU - Qiming, Zhouc

PY - 2006

Y1 - 2006

N2 - When spectral classification approach has lost its efficiency in object recognition from finer resolution imagery, texture plays more and more important role. This paper introduces an approach of using the combination of four kinds of texture measurements (grey mean value, standard deviation, edge point density, edge line density) to extracting residential areas from high-resolution imagery. The job of extraction is performed in three steps: (1) Extraction of candidate pixels of residential areas based on mean grey value and standard deviation; (2) Extraction of candidate areas of residential areas based on edge point density; (3) Verification of candidate areas of residential areas based on edge line density. An experiment by using IKONOS PAN image is given to verify the correct of the method.

AB - When spectral classification approach has lost its efficiency in object recognition from finer resolution imagery, texture plays more and more important role. This paper introduces an approach of using the combination of four kinds of texture measurements (grey mean value, standard deviation, edge point density, edge line density) to extracting residential areas from high-resolution imagery. The job of extraction is performed in three steps: (1) Extraction of candidate pixels of residential areas based on mean grey value and standard deviation; (2) Extraction of candidate areas of residential areas based on edge point density; (3) Verification of candidate areas of residential areas based on edge line density. An experiment by using IKONOS PAN image is given to verify the correct of the method.

KW - Edge line density

KW - Edge point density

KW - Grey mean value

KW - Residential areas

KW - Stand deviation

KW - Textures

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U2 - 10.1117/12.713248

DO - 10.1117/12.713248

M3 - Conference proceeding

AN - SCOPUS:33846232678

SN - 0819465283

SN - 9780819465283

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Geoinformatics 2006

T2 - Geoinformatics 2006: Remotely Sensed Data and Information

Y2 - 28 October 2006 through 29 October 2006

ER -

A texture-based approach for extracting residential areas from high-resolution imagery

Abstract

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Conference

Scopus Subject Areas

User-Defined Keywords

Access to Document

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