Image Fusion Techniques with Multiple-Sensors

Image Fusion Techniques with Multiple-Sensors

Yu-Jin Zhang (Department of Electronic Engineering, Tsinghua University, China)
Copyright: © 2015 |Pages: 11
DOI: 10.4018/978-1-4666-5888-2.ch586
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Background

There are many modalities for capture image and video, which use various sensors and techniques (Brakenhoff, et al., 1979; Committee, 1996; Bertero & Boccacci, 1998), such as visible light sensor (e.g., CCD, CMOS), infrared sensor, depth sensor (e.g., Kinect), con-focal scanning light microscopy (CSLM), a variety of computer tomography techniques (CT, ECT, SPECT), magnetic resonance imaging (MRI), synthesis aperture radar (SAR), millimeter wave radar (MMWR), etc.

Key Terms in this Chapter

Bayesian fusion: A probabilistic method for fusing information from different sensors. It is based on Bayes theory, and can be used both for feature level fusion and decision level fusion.

Objective evaluation of image fusion results: To judge the quality of image fusion with some computable metrics based on fusion results. For example, one approach is based on the singular value decomposition (SVD), in which the divergence of the singular value features between the source images and fused images is measured and the energy distortion of the fused image from input images is calculated.

Fusion based on rough set theory: A fusion method for decision level. Instead of exact set, it uses rough set to manipulate sensor data. It can compress redundant information so avoid the composition exploitation problem during fusion procedure.

Sensor model: An abstract representation of the physical sensors and its information manipulation process. Probabilistic sensor model is a typical example.

Subjective evaluation of image fusion results: To judge the quality of image fusion with subjects’ perception on fusion results.

Image Engineering (IE): An integrated discipline/subject comprising the study of all the different branches of image and video techniques. As a general term for all image techniques, it could be considered as a broad subject encompassing mathematics, physics, biology, physiology, psychology, electrical engineering, computer science, automation, etc. Its advances are also closely related to the development of telecommunications, biomedical engineering, remote sensing, document processing, industrial applications, etc.

Evidence reasoning fusion: A new method for fusing information from different sensors. It also called D-S theory. It has perfect performance in expression of uncertain knowledge, which is the reason why it has been making great progress in theory and application in recent years. It can be used both for feature level fusion and decision level fusion.

Information Fusion: Combined process of information from the source of same object or scene to obtain more complex, reliable and accurate information.

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