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Performance Assessment of Fusion Techniques

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Hyperspectral Image Fusion
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Abstract

A quantitative analysis enables understanding of various pros and cons of a fusion technique. A human observer can judge the performance of a fusion technique in terms of the visual quality of the fused image. However, this approach is completely subjective, and thus may vary for different observers. Different subjects can perceive the same image differently, and their perception may be based on several psycho-visual factors rather than an objective assessment of the scene. Also, this process turns out to be tedious, time-consuming, and yet not very accurate. An objective assessment of the image quality alleviates most of these problems associated with the subjective quality assessment. In this process of analyzing the quality of an image, several performance measures which can be calculated either from the image alone, or with reference to some other image are employed. These measures can be computed without any human intervention, and they do not get affected by any psycho-visual, or individual differences. An objective assessment, thus, provides a consistent outcome which facilitates comparison of different images. Although several attempts to quantify the useful information from the point of visualization have been made, there is no standardization in this process. Furthermore, most of these measures have been developed for generalized image fusion where only a few images are to be fused. In such cases, mathematical formulation of performance measures may be easy and intuitive. One can easily interpret the physical meaning of quantities and terms involved. However, this may not be the case when the number of constituent images increases. In this chapter, we extend some of these measures for an objective assessment of fusion of hyperspectral images. We also explain several modifications in the definitions of some of the existing measures in order to facilitate a better evaluation. We also explain the notion of consistency of a fusion technique to understand the behavior of a given technique when it is applied over a progressively increasing sets of images. We believe that the consistency analysis will help in deciding the suitability of a particular technique toward fusion of a large number of images.

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Correspondence to Subhasis Chaudhuri .

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© 2013 Springer Science+Business Media New York

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Chaudhuri, S., Kotwal, K. (2013). Performance Assessment of Fusion Techniques. In: Hyperspectral Image Fusion. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7470-8_9

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  • DOI: https://doi.org/10.1007/978-1-4614-7470-8_9

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7469-2

  • Online ISBN: 978-1-4614-7470-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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