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COMPLEX APPROACH FOR TEXTURE AND MULTISPECTRAL SEGMENTATION OF HIGH RESOLUTION SATTELITE IMAGES

Veselina Gospodinova

First published: 2011-06-20https://doi.org/10.5593/sgem2011/s08.102View metrics

Abstract

It is introduced a complex approach for texture and multispectral segmentation, based on texture analyses. The data fusion method is used for combining the multispectral and texture features of classes in the area s which is investigated. The texture features are estimated by the calculation of variance and skewness statistics over the windows with different sizes. The results ar e integrated with spectral chan nels of satellite images. The images from KOMPSAT-2 satellite are used for testing purposes. The spectral data are enhanced by "pan-sharpening" procedure that uses panchromatic channel. Therefore final multispectral data has the terrain element size of 1m. The analyses are provided by usage of EDRAS Imagine program package. Different combinations of spectral channels and channels with texture proper ties are combined and compared. The results of unsupervised classification are presented and analysed.

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Publication details

Title
COMPLEX APPROACH FOR TEXTURE AND MULTISPECTRAL SEGMENTATION OF HIGH RESOLUTION SATTELITE IMAGES
Authors
Veselina Gospodinova
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; SGEM2011 11th International Multidisciplinary Scientific GeoConference
Publisher
Stef92 Technology
Year
2011
Pages
Not available yet
ISSN
1314-2704
ISBN
Not available yet
Language
en
Publication type
Conference Paper
References9

  1. P.Chen & Th. Pavlidis. Segmentation by Texture Using a Co-Occurrence Matrix and a Split-and-Merge Algorithm, Computer graphics and Image Processing 10, 1979, pp.172-182

  2. M. Tuceryan & A. Jain. Texture An alysis, The Handbook of Pattern Recognition and Computer Vision (2nd Edition), pp 207-248, 1998.

  3. Wu Wenbo & Yao Jing & Kang Tingjun. Study of Remote Sensing Image Fusion and Its Application in Image Classificati on, Congress Beijing, vol. 37, pp.1141- 1145,

  4. X.Y.Hu & C.V.Tao & B.Prenzel. Automatic Segmentation of High-resolution Satellite Imagery by Integrati ng Texture, Intensity and Color Features, PhEngRS, vol.71, No. 12, December 2005, pp. 1399-1406.

  5. S.Todorovic & N.Ahuja. Texel-based Texture Segmentation, ICCV, Japan, 2009.

  6. J.Grim & P.Somol & M.Haindl & P.Pudil. Color Texture Segmentation by Decomposition of Gaussian Mixture Model, IAA, 2006, vol. 4225, pp 287-296.

  7. Dong-Cheon Lee & Toni Schenk. An adaptive approach for extracting texture information and segmentation, IAPhRS, Columbus, Ohio, Vol.32.

  8. J. Wang & W. Song & F. Gao. Imagery texture analysis based on multi-feature fractal dimension, ISPRS Congress Beijing, vol. 37, pp.569-573, 2008.

  9. Ani1 K. Jain & F. Farrokhnia. Unsupe rvised Texture Segmentation Using Gabor Filters, Journal Pattern Recognition archive, vol. 24, 1991.

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