1. How to submit my research paper? What’s the process of publication of my paper?
The journal receives submitted manuscripts via email only. Please submit your research paper in .doc or .pdf format to the submission email: jait@etpub.com.
2.Can I submit an abstract?
The journal publishes full research papers. So only full paper submission should be considered for possible publication. Papers with insufficient content may be rejected as well, make sure your paper is sufficient enough to be published...[Read More]

Classification of High Spatial Resolution Remote Sensing Images Based on Decision Fusion

Guizhou Wang 1, An Li 2, Guojin He 2, Jianbo Liu 2, Zhaoming Zhang 2, and Mengmeng Wang 2
1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
Abstract—With the development of earth observation technology, a series of high spatial resolution remote sensing satellites has been successfully launched. The earth observation data, especially high spatial resolution remote sensing image, is becoming more accessible. Therefore, the ability and efficiency of high spatial resolution remote sensing image classification has become a prominent problem for its further applications. This paper presents an object-based image classification framework based on decision fusion for high spatial resolution remote sensing image. This framework mainly included three steps. Firstly, high spatial resolution remote sensing image was segmented by multi-resolution segmentation method. Secondly, the multi-source features of segmented regions were extracted and classified by Support Vector Machine classifier, respectively. Finally, the multi-source classification results were integrated by decision fusion and reclassification strategy. Quick-bird satellite data was performed to classify the land surface using the proposed classification framework; and the classification results using different feature spaces were compared. The results show that the classification method based on decision fusion takes fully advantage of multi-source region features and finally obtain higher classification precision.

Index Terms—high spatial resolution remote sensing image, image segmentation, image classification, decision fusion

Cite: Guizhou Wang, An Li, Guojin He, Jianbo Liu, Zhaoming Zhang, and Mengmeng Wang, "Classification of High Spatial Resolution Remote Sensing Images Based on Decision Fusion," Vol. 8, No. 1, pp. 42-46, February, 2017. doi: 10.12720/jait.8.1.42-46
Copyright © 2013-2016 Journal of Advances in Information Technology, All Rights Reserved
E-mail: jait@etpub.com