Approach of Texture Signature Determination - Application to Forest Cover Classification of High Resolution Satellite Image

被引:0
作者
Zaaboub, Wala [1 ]
Ben Dhiaf, Zouhour [1 ]
机构
[1] FST, Lab Comp Sci Programming Algorithm & Heurist, Tunis, Tunisia
来源
2014 6TH INTERNATIONAL CONFERENCE OF SOFT COMPUTING AND PATTERN RECOGNITION (SOCPAR) | 2014年
关键词
texture signature; classification; sum and difference histogram; high resolution satellite image; multifractal; NATURAL IMAGES;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper presents an approach of textural signature identification for the classification of high resolution satellite image of forest. We are looking for the most appropriate combination of features from texture measures. This combination which forms our signature should allow the discrimination between different types of textures present in the image that will be classified. We improve our signature by a step of weighting features. The weight of each feature reflects its degree of confidence. We finish with an experimental step which is an application of our combined weighted signature for the purposes of classification of high resolution satellite image of forest.
引用
收藏
页码:325 / 330
页数:6
相关论文
共 50 条
[21]   A design of category classification system for high resolution satellite [J].
Nakano, M ;
Kalpoma, KA ;
Nakamura, T ;
Kudoh, J .
IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET, 2004, :4516-4518
[22]   STRUCTURAL HIGH-RESOLUTION SATELLITE IMAGE INDEXING [J].
Xia, Gui-Song ;
Yang, Wen ;
Delon, Julie ;
Gousseau, Yann ;
Sun, Hong ;
Maitre, Henri .
100 YEARS ISPRS ADVANCING REMOTE SENSING SCIENCE, PT 1, 2010, 38 :298-303
[23]   A Simple Approach for Mapping Forest Cover from Time Series of Satellite Data [J].
Liu, Yang ;
Liu, Ronggao .
REMOTE SENSING, 2020, 12 (18)
[24]   Performances of Frequency-based Contextual Classifier in Land Use/Cover Classification using High Resolution Satellite Images [J].
Mustapha, M. R. ;
Lim, H. S. ;
MatJafri, M. Z. ;
Hassan, F. M. .
MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL REMOTE SENSING TECHNOLOGY, TECHNIQUES, AND APPLICATIONS III, 2010, 7857
[25]   Application of Neural Network Technologies for the Classification of Cloudiness by Texture Parameters of MODIS High-Resolution Images [J].
Astafurov, V. G. ;
Skorokhodov, A. V. .
IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2019, 55 (09) :1012-1021
[26]   Application of Neural Network Technologies for the Classification of Cloudiness by Texture Parameters of MODIS High-Resolution Images [J].
V. G. Astafurov ;
A. V. Skorokhodov .
Izvestiya, Atmospheric and Oceanic Physics, 2019, 55 :1012-1021
[27]   Automatic Road Extraction using High Resolution Satellite Image Based on Texture Progressive Analysis and Normalized Cut Method [J].
Senthilnath, J. ;
Rajeshwari, M. ;
Omkar, S. N. .
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2009, 37 (03) :351-361
[28]   Fusion of low resolution optical and high resolution SAR data for land cover classification [J].
Törmä, M ;
Lumme, J ;
Patrikainen, N ;
Luojus, K .
IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET, 2004, :2680-2683
[29]   Classification of high-resolution satellite images using supervised locality preserving projections [J].
Chen, Yen-Wei ;
Han, Xian-Hua .
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS, 2008, 5178 :149-156
[30]   An object-specific image texture analysis of H-resolution forest imagery [J].
Hay, GJ ;
Niemann, KO ;
McLean, GF .
REMOTE SENSING OF ENVIRONMENT, 1996, 55 (02) :108-122