Different approaches for the texture classification of a remote sensing image bank

Philippe Durand; Gerard Brunet; Dariush Ghorbanzadeh; Luan Jaupi

doi:10.1117/12.2302497

10 April 2018 Different approaches for the texture classification of a remote sensing image bank

Philippe Durand, Gerard Brunet, Dariush Ghorbanzadeh, Luan Jaupi

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061530 (2018) https://doi.org/10.1117/12.2302497
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

In this paper, we summarize and compare two different approaches used by the authors, to classify different natural textures. The first approach, which is simple and inexpensive in computing time, uses a data bank image and an expert system able to classify different textures from a number of rules established by discipline specialists. The second method uses the same database and a neural networks approach.

Citation Download Citation

Philippe Durand, Gerard Brunet, Dariush Ghorbanzadeh, and Luan Jaupi "Different approaches for the texture classification of a remote sensing image bank", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061530 (10 April 2018); https://doi.org/10.1117/12.2302497

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available