Efficient Land-cover Segmentation Using Meta Fusion
Journal Title: Journal of Information Systems and Telecommunication - Year 2016, Vol 4, Issue 3
Abstract
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.
Authors and Affiliations
Hadi Mahdipour Hossein Abad, Morteza Khademi, Hadi Sadoghi Yazdi
Keywords
Related Articles
- EP ID EP184044
- DOI 10.7508/jist.2016.03.003
- Views 118
- Downloads 0
Hybrid Task Scheduling Method for Cloud Computing by Genetic and PSO Algorithms
Cloud computing makes it possible for users to use different applications through the internet without having to install them. Cloud computing is considered to be a novel technology which is aimed at handling and providi...
Improved Generic Object Retrieval In Large Scale Databases By SURF Descriptor
Normally, the-state-of-the-art methods in field of object retrieval for large databases are achieved by training process. We propose a novel large-scale generic object retrieval which only uses a single query image and t...
Fast Automatic Face Recognition from Single Image per Person Using GAW-KNN
Real time face recognition systems have several limitations such as collecting features. One training sample per target means less feature extraction techniques are available to use. To obtain an acceptable accuracy, mos...
Tracking Performance of Semi-Supervised Large Margin Classifiers in Automatic Modulation Classification
Automatic modulation classification (AMC) in detected signals is an intermediate step between signal detection and demodulation, and is also an essential task for an intelligent receiver in various civil and military app...
An Ultra-Wideband Common Gate LNA With Gm-Boosted And Noise Canceling Techniques
In this paper, an ultra-wideband (UWB) common gate low-noise amplifier (LNA) with gm-boosted and noise-cancelling techniques is presented. In this scheme we utilize gm-boosted stage for cancelling the noise of matching d...