Computational imaging provides comprehensive and reliable information about human tissue for medical diagnosis and treatment, with medical image fusion as one of the most important technologies in the field. Empirical mode decomposition (EMD), a promising model for image processing, has been used for image fusion in some methods. However, the varying number of decomposed layers leads to problems using EMD for image fusion. In this article, we propose a fusion method for medical images incorporating $L2$ -norm-based features, a match/salience/fuzzy-weighted measure, and the 2-D Littlewood–Paley empirical wavelet transform (2-D LPEWT) as new version of EMD. We first decompose medical images with LPEWT to obtain the residual component (residue) and detailed sub-images that are named as intrinsic mode functions (IMFs). Then we extract the regional features of residue with an $L2$ -norm-based model to fuse the residue while simultaneously fusing IMFs using a method combining a fuzzy membership function with a match/salience measurement. Finally, we reconstruct the comprehensive image by applying inverse LPEWT to the fused residue and IMFs. We evaluated our method using a frequently-used data set of brain images. The results show that our proposed method is more effective than conventional methods by fusing more information into the final images. We also show a feasible scheme for applying EMD to image fusion.

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Brain Medical Image Fusion Using L2 -Norm-Based Features and Fuzzy-Weighted Measurements in 2-D Littlewood–Paley EWT Domain

Image fusion is a technique to integrate different advantages of different images with the same scene. A method called empirical mode decomposition is introduced at first. For each pair of intrinsic mode functions, which are the components of two functions obtained by empirical mode decomposition, are fused by certain fusion rule. The final fusion result is acquired by the inverse empirical mode decomposition method. Experimental result shows that the proposed method is effective and promising.

Image fusion method based on EMD method

Mode instability phenomenon acts as a common feature in single-frequency fiber ring lasers. Pump power and cavity length are two important control parameters affecting the output SLM stability. In this work, mode instability of an EDFRL has been experimentally investigated by utilizing two effective methods. On the whole, a mode stability map of the EDFRL scaled by pump coefficient is measured and discussed completely through the interferometer scheme, which helps to evaluate the mode stability dependent on pump power in a form of global visualization. Besides, real-time and detailed detection of various mode instability behaviors, including occasional mode hopping, periodic mode hopping and intermittent MLM oscillation, is carried out using the optical heterodyne scheme. The dynamics of mode instability can also be visualized by on-line time-frequency diagrams. This work will contribute to the analysis, understanding and suppression of mode hopping in fiber ring lasers.

Yubo Xie

Papers

Image fusion method based on EMD method

Experimental investigation on mode instability phenomenon of a fiber ring laser