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What is Information Fusion

Encyclopedia of Information Science and Technology, Second Edition
Combined process of information from the source of same object or scene to obtain more complex, reliable and accurate information.
Published in Chapter:
Information Fusion of Multi-Sensor Images
Yu-Jin Zhang (Tsinghua University, Beijing, China)
DOI: 10.4018/978-1-60566-026-4.ch307
The human perception to the outside world is the results of action among brain and many organs. For example, the intelligent robots that people currently investigate can have many sensors for sense of vision, sense of hearing, sense of taste, sense of smell, sense of touch, sense of pain, sense of heat, sense of force, sense of slide, sense of approach (Luo, 2002). All these sensors provide different profile information of scene in same environment. To use suitable techniques for assorting with various sensors and combining their obtained information, the theories and methods of multi-sensor fusion are required. Multi-sensor information fusion is a basic ability of human beings. Single sensor can only provide incomplete, un-accurate, vague, uncertainty information. Sometimes, information obtained by different sensors can even be contradictory. Human beings have the ability to combine the information obtained by different organs and then make estimation and decision for environment and events. Using computer to perform multi-sensor information fusion can be considered as a simulation of the function of human brain for treating complex problems. Multi-sensor information fusion consists of operating on the information data come from various sensors and obtaining more comprehensive, accurate, and robust results than that obtained from single sensor. Fusion can be defined as the process of combined treating of data acquired from multiple sensors, as well as assorting, optimizing and conforming of these data to increase the ability of extracting information and improving the decision capability. Fusion can extend the coverage for space and time information, reducing the fuzziness, increasing the reliability of making decision, and the robustness of systems. Image fusion is a particular type of multi-sensor fusion, which takes images as operating objects. In a more general sense of image engineering (Zhang, 2006), the combination of multi-resolution images also can be counted as a fusion process. In this article, however, the emphasis is put on the information fusion of multi-sensor images.
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Image Analysis and Understanding Based on Information Theoretical Region Merging Approaches for Segmentation and Cooperative Fusion
Combination of data from multiple sources and gather that information into discrete, actionable items in order to achieve inferences, which will be more efficient and narrowly tailored than if they were achieved by means of disparate sources. In computer vision, image fusion is the process of combining relevant information from two or more images into a single image. The resulting image will be more informative than any of the input images.
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Tanimoto Similarity Coefficients Measuring Bipolar q-Rung Picture Fuzzy Information and Their Applications
Fusion can be described as a process of merging information from multiple sources to produce the most specific and comprehensive unified data about an activity, entity or event. Information fusion involves the combination of information into a new set of information towards reducing redundancy and uncertainty.
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Computational Methods and Tools for Decision Support in Biomedicine: An Overview of Algorithmic Challenges
The utilization of all available information at multiple abstraction levels (measurements, features, decisions) to maximize an expert system’s performance.
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Image Fusion Techniques with Multiple-Sensors
Combined process of information from the source of same object or scene to obtain more complex, reliable and accurate information.
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