The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
A region-based multi-sensor image fusion scheme using pulse-coupled neural network
Pattern Recognition Letters
Guest editorial: Image fusion: Advances in the state of the art
Information Fusion
Pixel-based and region-based image fusion schemes using ICA bases
Information Fusion
Multifocus image fusion using region segmentation and spatial frequency
Image and Vision Computing
An Image Fusion Method Based on WNMF and Region Segmentation
PACIIA '08 Proceedings of the 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application - Volume 02
Multifocus image fusion using the nonsubsampled contourlet transform
Signal Processing
A Novel Region Based Multifocus Image Fusion Method
ICDIP '09 Proceedings of the International Conference on Digital Image Processing
Pixel-level image fusion with simultaneous orthogonal matching pursuit
Information Fusion
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Combined morphological-spectral unsupervised image segmentation
IEEE Transactions on Image Processing
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In this paper, we propose an image-driven regional fusion method based on a specific region partition strategy according to the redundant and complementary correlation of the input images. Different from the traditional regional fusion approaches dividing one or more input images, our final region map is generated from the similarity comparisons between source images. Inspired by the success of structural similarity index (SSIM), the similarity characteristics of source images are represented by luminance, contrast, and structure comparisons. To generate redundant and complementary regions, we over segment the SSIM map using watershed, and merge the small homogeneous regions with close correlation based on the similarity components. In accordance with the concentrated similarity of different regions, the fusion principles for special regions are constructed to combine the redundant or complementary property. In our method, the redundant and complementary regions of input images are distinguished effectively, which can aid in the sequent fusion process. Experimental results demonstrate that our approach achieve superior results in the different fusion applications. Compared with the existing work, the proposed approach outperforms in both visual presentation and objective evaluation.