Name
Abstract | ||
|---|---|---|
Accurate image fusion is an essential technique to obtain more information from remote sensing image in different sensors. This paper presents a method for fusion delineating objects from multiple sensors. The proposed algorithm partitions feature-based mutual information into the maximization as the requirement for fusion, which consists of entropy in the image. The wavelet transform decomposes the maximum value of the mutual information for image fusion. To evaluate the validity of the proposed method, experiments were conducted using two types of remote sensing images. The overlapping, correctness, and quality of the fusion object are over 98 %, 95.3 %, and 95.1 % respectively, which proves the proposed method is a promising solution for registration and fusion from two remote sensing images. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-48036-7_33 | INTELLIGENT AUTONOMOUS SYSTEMS 14 |
Keywords | Field | DocType |
Image registration,Image fusion,Mutual information,Entropy,Wavelet transform,Multiple sensors | Pattern recognition,Image fusion,Computer science,Correctness,Fusion,Artificial intelligence,Mutual information,Maximization,Image registration,Wavelet transform,Wavelet | Conference |
Volume | ISSN | Citations |
531 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yulong Liu | 1 | 6 | 4.48 |
| Yiping Chen | 2 | 16 | 7.69 |
| Wang Cheng | 3 | 103 | 20.70 |
| Ming Cheng | 4 | 54 | 13.93 |