Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Contour extraction of moving objects in complex outdoor scenes
International Journal of Computer Vision
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
A flexible framework for local phase coherence computation
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
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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.