Model Of Multi-source Image Fusion For Anti-interference Based On Brightness Variation Metric

In today's highly advanced information age, information processing has become a task of vital importance related to the national economy and the people's livelihood. Information processing is a process of identifying and classifying information, and it can enhance the effectiveness of information and anti-interference capabilities, which can also improve the subjective senses of the information. And the processed information will be more helpful to the life and the production of people, and help them to make the right analysis and decision. Multi-source image fusion is an information fusion process, which can integrate multi-sensor images' information, eliminate the interference signal, and enhance the resolution and the visual effects of fused images. Via multi-source image fusion, better images with high-quality and reliability target scenes can be generated from images producted by different sensors. Multi-source image fusion has become a hot research field of image processing, and widely used in many areas of national economic construction, such as national defense, medical, aerospace, industrial and agricultural production, security monitoring, disaster relief, people's livelihood, and etc.The anti-interference multi-source image fusion takes the advantage of the complementary information from different sensors, integrates the images, highlights the target information, and generates a fusion image with higher availability according to a certain integration requirement. This paper analyzed the current research status, researched to the related theories and technologies, contrasted a variety of major multi-scale decomposition analysis tools and integration algorithms of image fusion, and explored the imaging properties of clouds, proposed a set of multi-source image fusion model which is anti-cloud interference, put forward the fusion calculation formula with verification. A cloud detector based on brightness variation metric was proposed. The paper explored the characteristics of clouds imaging in the visible and infrared images, summarized the law of cloud imaging and proposed the concept of the brightness variation metric combining the local variance with the local gradient, and the metric can represent the local characteristics of cloud imaging.The anti-cloud interference image fusion model for visible and infrared images based on brightness variation metric was proposed. By multiscale analysis the visible and infrared images were decomposed, and the decomposed componets were fused based on brightness variation metric respectively. Then through two sets of experiments we compared and verified the validity, accuracy and superiority of the model.The anti-cloud interference image fusion model for multi-sensor images based on brightness variation metric was proposed. The model of image fusion based on brightness variation metric for two sources is extended to three sources, and the extended model was verified through simulation experiments. And thenthe model of image fusion based on brightness variation metric was extended to multiple sources, that is, not limited to the number of image sources. The fusion formulas of the proposed new model were given, analyzed,and discussed, as a result, the new model unified with the fusion formulas of two sources and three sources and formed a set of complete, general computational formulas.