16 September 2005 The Renyi entropy as a decision measure for a pseudo-Wigner distribution image fusion framework
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Renyi entropy is receiving an important attention as a data analysis tool in many practical applications, due to its relevant properties when dealing with time-frequency representations (TFR). It's characterized for providing a generalized information content (entropy) of a given signal. The use of Renyi entropy can be extended to spatial-frequency applications. In this paper we present results of applying the Renyi entropy to an image fusion method, recently developed by the authors, based on the use of a 1-D pseudo-Wigner distribution (PWD). The fused image is obtained after the application of a Renyi entropy measure to the point-wise PWD of the images. The Renyi measure allow us to individually identify, from an entropic criterion, which pixels have a higher amount of information among the given input images. The method is illustrated with diverse related images of the same scene, with different amount of spatial-variant degradation or coming from different sources. In addition to that, some numerical results are presented, providing in this way a quantitative estimate of the accuracy of the fusion method.
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Salvador Gabarda, Salvador Gabarda, Gabriel Cristobal, Gabriel Cristobal, "The Renyi entropy as a decision measure for a pseudo-Wigner distribution image fusion framework", Proc. SPIE 5910, Advanced Signal Processing Algorithms, Architectures, and Implementations XV, 59100E (16 September 2005); doi: 10.1117/12.617269; https://doi.org/10.1117/12.617269


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