A perceptual image fusion method is proposed that employs explicit luminance and contrast masking models. These models are combined to give the perceptual importance of each coefficient produced by the dual-tree complex wavelet transform of each input image. This combined model of perceptual importance is used to select which coefficients are retained and furthermore to determine how to present the retained information in the most effective way. This paper is the first to give a principled approach to image fusion from a perceptual perspective. Furthermore, the proposed method is shown to give improved quantitative and qualitative results compared with previously developed methods.
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