Mendeley
TY  _  JOUR
ID  -  139507081116403465
TI  -  Efficient Land-cover Segmentation Using Meta Fusion	
JO  -  Journal of Information Systems and Telecommunication (JIST) 
JA  -  ES
LA  -  en
SN  -  2322-1437
AU  -  خادمی مرتضی
AU  -  Sadoghi yazdi	 Hadi
AD  -  دانشگاه فردوسی مشهد
AD  -  Ferdowsi University of Mashhad
Y1  -  2016
PY  -  2016
VL  -  15
IS  -  4
SP  -  1
EP  -  10
KW  -  Fusion

KW  -   Land-cover Segmentation

KW  -   Multiple High-spatial Resolution Panchromatic Remotely Sensed (HR-PRS) Images

KW  -   Fuzzy C-means (FCM)
DO  -  
N2  -  Most popular fusion methods have their own limitations; e.g. OWA (order weighted averaging) has “linear model” and “summation of inputs proportions in fusion equal to 1” limitations. Considering all possible models for fusion, proposed fusion method involve input data confusion in fusion process to segmentation. Indeed, limitations in proposed method are determined adaptively for each input data, separately. On the other hand, land-cover segmentation using remotely sensed (RS) images is a challenging research subject; due to the fact that objects in unique land-cover often appear dissimilar in different RS images. In this paper multiple co-registered RS images are utilized to segment land-cover using FCM (fuzzy c-means). As an appropriate tool to model changes, fuzzy concept is utilized to fuse and integrate information of input images. By categorizing the ground points, it is shown in this paper for the first time, fuzzy numbers are need and more suitable than crisp ones to merge multi-images information and segmentation. Finally, FCM is applied on the fused image pixels (with fuzzy values) to obtain a single segmented image. Furthermore mathematical analysis and used proposed cost function, simulation results also show significant performance of the proposed method in terms of noise-free and fast segmentation.
UR  - rimag.ir/ar/Article/14954
L1  - rimag.ir/ar/Article/Download/14954
ER  -  
