Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor.

[Fusion of dual color MWIR images based on support value transform and top-hat decomposition].

Fusion method of dual color mid-wave infrared images is presented in this paper in order to solve such frequently rising issues as limited contrast ratio improvement and serious marginal area distortion in the fusion of the above two images using multi-scale top-hat decomposition. The detailed procedure is shown as the following: A low-frequency component image and a sequence of support value images of the two subdivision band images of mid-wave infrared are obtained respectively with support value transform. Multi-scale bright and dim information are first extracted from the last layer of low-frequency image using the multi-scale top-hat decomposition method respectively.