Statistical approach for Segmentation of satellite image with Markov random field Model

被引：1

作者：

Bouchti, Jamal ^{[1
]}

Asselman, Adel ^{[1
]}

El Hajjaji, Abdellah ^{[2
]}

机构：

[1] Fac Sci, Opt & Photon Team, Mhannech Ii 93002, Tetuan, Morocco

[2] Fac Sci, Syst Commun & Detect Lab, Mhannech Ii 93002, Tetuan, Morocco

来源：

ICCWCS'17: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTING AND WIRELESS COMMUNICATION SYSTEMS | 2017年

关键词：

Image segmentation; Markov random field; Gibbs distribution; Potential energy function; iterative algorithm;

D O I：

10.1145/3167486.3167550

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Satellite imagery is one of the wide areas in segmentation. They are used for Analysis of the different elements of the landscapes such as cropland, bare land, forests, flooded areas, assists in vegetation, disease detection, facilitates monitoring of deforestation and desertification, as well as the evolution of infrastructure in inhabited areas or the sea ice. In this paper, we propose an image segmentation method based on Markov random field model and Gibbs distributions, we introduce iterative algorithm process to minimize an energy function.

引用

页数：4

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