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To my parents Tianyun Liu and Yuanyuan Li. iv ACKNOWLEDGMENTS I would like to thank my major advisor Professor Jan P. Allebach to giving me the opportunity to work with him. Without his tremendous help, advice, and especially encouragement, this research would not have happened.I also would like to thank our research sponsors, the Hewlett-Packard Company, which gives us generous support, without whom the research would not be possible.I would like to thank all EISL members for their wonderful collaboration. You support me greatly and were always willing to help me.Lastly, I would also like to thank my parents for their love and support.

Fusion of images from different imaging modalities, obtained by conventional fusion methods, may cause artifacts, including destructive superposition and brightness irregularities, in certain cases. This paper proposes two methods for improving image multimodal fusion quality. Based on the finding that a better fusion can be achieved when the images have a more positive correlation, the first method is a decision algorithm that runs at the preprocessing fusion stage and determines whether a complementary gray level of one of the input images should be used instead of the original one. The second method is suitable for multiresolution fusion, and it suggests choosing only one image from the lowest-frequency sub-bands in the pyramids, instead of combining values from both sub-bands. Experimental results indicate that the proposed fusion enhancement can reduce fusion artifacts. Quantitative fusion quality measures that support this conclusion are shown.

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