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[Display omitted] • Firstly, the local linear model established in this paper presents the gradient information of the VIS image as the pixel intensity of the IR image. • Secondly, the detail perception factor and contrast control factor are introduced into the design of the cost function, which has the effect of enhancing contrast and suppressing noise moderately • Finally, this paper adopts the strategy of dual-scale decomposition to obtain infrared features and combine them with the initial fusion results. This scheme enriches the detailed texture information from the IR image in the fusion result. Infrared (IR) and visible (VIS) images represent the features of the scene at different wavelengths, and the features they contain have different properties. Therefore, the traditional weighted fusion strategy is challenging to preserve the different types of feature information. In addition, VIS images are highly susceptible to bad weather, which also seriously affects the quality of fused images in complex environments. To solve the above problems, we propose a feature enhancement fusion method. First, a fusion model called contrast enhancement guided filter (CEGF) is proposed. The new model enables the texture information of VIS images to be presented with the intensity of infrared pixels, which solves the problem of combining different attribute features and removes the influence of harsh lighting conditions. To improve the visibility of texture details under different lighting conditions, a contrast modulation factor is added to the cost function design of the filter to enhance the contrast of visible details. Second, we use a dual-scale decomposition strategy to enhance the infrared feature information of the fusion results. Finally, we apply the method of this paper with ten classical image fusion algorithms in two types of datasets. The visual effect and objective evaluation of the fusion results verify that the proposed method preserves the characteristics of the high contrast of IR images and improves the visibility of infrared scenes for subsequent target identification and detection. [ABSTRACT FROM AUTHOR]

In order to improve the spatial resolution of an optical micro-scanning thermal microscope system, the micro-scanning position must be accurately calibrated. An adaptive calibration method based on image registration and plane coordinate system is proposed. The meaning of calibration is given, and the principle and method of point calibration are introduced in detail and experiments using the real system were done. Different reconstruction methods were applied to reconstruct the visible light image and the real thermal microscope image, and the evaluation scores are given. Results of simulation and real thermal imaging processing show that the method can successfully calibrate the micro-scanning position. The method can significantly improve the oversampled reconstructed image quality, thus enhancing the spatial resolution of the system. This method can also be used in other electro-optical imaging systems. [ABSTRACT FROM AUTHOR]