摘要
In this paper, an image fusion method based on two-dimensional principal component analysis (2DPCA) is proposed. The proposed method adopts 2DPCA to trans-form infrared and visible images into feature domain. Then, extracted features are divided into principal part and minor part based on their importance. There is only need to calculate the principal part, minor part can be obtained by sub-tracting principal part from original image so that the amount of calculation can be reduced. Each part is then fused by different fusion rule. Finally, the fusion image is constructed by adding fused principal image and fused mi-nor image. The performance of proposed method is evaluated with four quality metrics. Experimental results show that the proposed method outperforms the state of the art multi-resolution methods.
| 源语言 | 英语 |
|---|---|
| 页 | 596-600 |
| 页数 | 5 |
| DOI | |
| 出版状态 | 已出版 - 2013 |
| 活动 | 2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 - Naha, Okinawa, 日本 期限: 5 11月 2013 → 8 11月 2013 |
会议
| 会议 | 2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 |
|---|---|
| 国家/地区 | 日本 |
| 市 | Naha, Okinawa |
| 时期 | 5/11/13 → 8/11/13 |
指纹
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