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
  • [1] Application of Texture Analysis in Land Cover Classification of High Resolution Image
    Shen, Guangrong
    Sarris, Apostolos
    FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 3, PROCEEDINGS, 2008, : 513 - +
  • [2] Texture feature fusion for high resolution satellite image classification
    Zhao, YD
    Zhang, LP
    Li, PX
    Computer Graphics, Imaging and Vision: New Trends, 2005, : 19 - 23
  • [3] Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery
    Kim, So-Ra
    Lee, Woo-Kyun
    Kwak, Doo-Ahn
    Biging, Greg S.
    Gong, Peng
    Lee, Jun-Hak
    Cho, Hyun-Kook
    SENSORS, 2011, 11 (02): : 1943 - 1958
  • [4] A multiresolution approach for texture classification in high resolution satellite imagery
    Cerra, Daniele
    Datcu, Mihai
    RIVISTA ITALIANA DI TELERILEVAMENTO, 2010, 42 (01): : 13 - 24
  • [5] IMAGE CLASSIFICATION: A NOVEL TEXTURE SIGNATURE APPROACH
    He, Wenda
    Zwiggelaar, Reyer
    2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, : 2725 - 2728
  • [6] Land cover classification of high-resolution image based on texture analysis
    Shen, Guangrong
    Sarris, Apostoles
    PROGRESS OF INFORMATION TECHNOLOGY IN AGRICULTURE, 2007, : 674 - 679
  • [7] A Review of Satellite Missions and Forest Cover Classification Methods Using High Resolution Satellite Imagery
    Deur, Martina
    Gasparovic, Mateo
    Balenovic, Ivan
    GEODETSKI LIST, 2021, 75 (02) : 143 - 168
  • [8] CLASSIFICATION OF FOREST STRUCTURE USING VERY HIGH RESOLUTION PLEIADES IMAGE TEXTURE
    Beguet, B.
    Chehata, N.
    Boukir, S.
    Guyon, D.
    2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014, : 2324 - 2327
  • [9] A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification
    Yu, Huai
    Yang, Wen
    Xia, Gui-Song
    Liu, Gang
    REMOTE SENSING, 2016, 8 (03)
  • [10] Spectral-texture classification of high resolution satellite images for the state forest inventory in Russia
    Dmitriev, Egor V.
    Sokolov, Anton A.
    Kozoderov, Vladimir V.
    Delbarre, Herve
    Melnik, Petr G.
    Donskoi, Sergey A.
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XXI, 2019, 11149
12345