Target Fusion Algorithm for Remote Sensing Image Recognition
Multisource image fusion technology is widely applied in a variety of fields such as remote sensing, computer vision, medical diagnosis and military surveillance. In most instances, multispectral and panchromatic images can provide more complementary information for feature extraction. Two kinds of images are used for target recognition. Algorithms based on gradient for image fusion only consider high-frequency information changes of the images, and neglect the richness of high-frequency information. To solve this problem, a new kind of self-adaptive rule and algorithm based on gradient and energy is proposed in this paper by analyzing the internal relations between the statistics and the content of the images. The rule and algorithm take into account the changes in high-frequency information and the richness of high-frequency information, and guarantees the richness of image information. Experiments show that the fusion rule and algorithm can significantly preserve all useful information from primitive images and effectively recognize targets with higher recognition accuracy.
gradient energy local statistics data fusion
Zhang Yong-mei Ma Li
School of Information Engineering,North China University of Technology , Beijing,China School of Information Engineering,North China University of Technology ,Beijing, China
国际会议
三亚
英文
1075-1078
2012-01-06（万方平台首次上网日期，不代表论文的发表时间）