In many actual applications, fused image is essential to contain high-quality details for achieving a comprehensive representation of the real scene. However, existing image fusion methods suffer from loss of details because of the error accumulations of sequential tasks. This paper proposes a novel fusion method to preserve details of infrared and visible images by combining new decomposition, feature extraction, and fusion scheme. For decomposition, different from the most decomposition methods by guided filter, the guidance image contains only the strong edge of the source image but no other interference information so that rich tiny details can be decomposed into the detailed part. Then, according to the different characteristics of infrared and visible detail parts, a rough convolutional neural network (CNN) and a sophisticated CNN are designed so that various features can be fully extracted. To integrate the extracted features, we also present a multi-layer features fusion strategy through discrete cosine transform (DCT), which not only highlights significant features but also enhances details. Moreover, the base parts are fused by weighting method. Finally, the fused image is obtained by adding the fused detail and base part. Different from the general image fusion methods, our method not only retains the target region of source image but also enhances background in the fused image. In addition, compared with state-of-the-art fusion methods, our proposed fusion method has many advantages, including (i) better visual quality of fused-image subjective evaluation, and (ii) better objective assessment for those images.

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Imaging brain microvasculature is important in plasticity studies of cerebrovascular diseases. Applying contrast agents, traditional μCT and μMRI methods gain imaging contrast for vasculature. The aim of this study is to develop a synchrotron radiation X-ray inline phase-contrast tomography (SRXPCT) method for imaging the intact mouse brain (micro)vasculature in high resolution (~3.7 μm) without contrast agent. A specific preparation protocol was proposed to enhance the phase contrast of brain vasculature by using density difference over gas-tissue interface. The CT imaging system was developed and optimized to obtain 3D brain vasculature of adult male C57BL/6 mice. The SRXPCT method was further applied to investigate the microvasculature changes in mouse brains (n = 14) after 14-day reperfusion from transient middle cerebral artery occlusion (tMCAO). 3D reconstructions of brain microvasculature demonstrated that the branching radius ratio (post- to preinjury) of small vessels (radius < 7.4 μm) in the injury group was significantly smaller than that in the sham group (p < 0.05). This result revealed the active angiogenesis in the recovery brain after stroke. As a high-resolution and contrast-agent-free method, the SRXPCT method demonstrates higher potential in investigations of functional plasticity in cerebrovascular diseases.

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