Abstract
Image fusion is the task of enhancing the perception of a scene by combining information captured by different imaging sensors. A critical issue in the design of image fusion algorithms is to define activity measures that can evaluate and compare the local information content of multiple images. In doing so, existing methods share a common assumption that high local energy or contrast is a direct indication for local sharpness. In practice, this assumption may not hold, especially when the images are captured using different instrument modalities. Here we propose a complex wavelet transform domain local phase coherence measure to assess local sharpness. A novel image fusion method is then proposed to achieve both maximal contrast and maximal sharpness simultaneously at each spatial location. The proposed method is computationally efficient and robust to noise, which is demonstrated using both synthetic and real images.
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Hassen, R., Wang, Z., Salama, M. (2009). Multifocus Image Fusion Using Local Phase Coherence Measurement. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_6
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DOI: https://doi.org/10.1007/978-3-642-02611-9_6
Publisher Name: Springer, Berlin, Heidelberg
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