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The Degree of Linear Polarization (DoLP) is a key dimension of information in polarization imaging. The quality of polarization images is greatly affected by imaging equipment and environmental factors. Therefore, an enhancement method for the DoLP image is proposed in this paper. First, a super-resolution reconstruction algorithm based on the Detail Enhancement Guided Image Filter is proposed to solve the problem of mosaicization and pseudo-polarization information caused by the degradation of spatial resolution and super-resolution reconstruction of DoFP imaging. Second, for the problem of rapid degradation of polarization image quality caused by hazy environment, a DoLP enhancement algorithm based on multi-channel difference Signal-to-Noise Ratio is proposed to improve the visual effect of polarization images in different scenes with hazy environment. The method proposed in this paper implements super-resolution reconstruction, demosaicing, pseudo-polarization information removal, and adaptive enhancement of DoLP images in DoFP systems. [ABSTRACT FROM AUTHOR]

Wood structural timbers at three locations (eave, beam frame, and column) were exploited to elucidate the deterioration state and mechanism of historical timber structures from the Yunnan Military Academy (Kunming, Yunnan Province). The morphological structures, physical and mechanical characteristics, and chemical components were measured to illustrate the deterioration state and elucidate the degradation mechanism. The results demonstrated that the deterioration of structural timbers was closely dependent on their locations in the architecture. The outside eave was in the worst deterioration state, which was caused by natural factors (ultraviolet rays, rain, and fungi), resulting in severe distortion of wood structures and a significant reduction in basic density and compressive strength. Significant carbohydrate losses that occurred in the eave and beam frame were mainly contributed by the brown rot fungi, predominantly due to the frequently wet condition and humid environment. Moreover, column structures were mainly attacked by insects (weevils) due to their location near the ground, accordingly in an obvious decline in mechanical properties. Collectively, structural timbers exhibited different deterioration states contributed by the degradation mechanism, predominantly influenced by their locations in architecture. [ABSTRACT FROM AUTHOR]

Infrared imaging theory is an important theoretical basis for the design of infrared imaging systems, but there is no research on infrared imaging theory for designing thermal microscope imaging systems. Therefore, we studied the performance evaluation and optimization theory of thermal microscope imaging systems. In this paper, we analyzed the difference in spectral radiant flux between thermal microscope imaging and telephoto thermal imaging. The expression of signal-to-noise ratio of the output image of the thermal microscope imaging systems was derived, based on the analysis of the characteristics of thermal microscope imaging. We studied the performance evaluation model of thermal microscope imaging systems based on the minimum resolvable temperature difference and the minimum detectable temperature difference. Simulation and analysis of different detectors (ideal photon detector and ideal thermal detector) were also carried out. Finally, based on the conclusion of theoretical research, we carried out a system design and image acquisition experiment. The results show that the theoretical study of thermal microscope imaging systems in this paper can provide reference for the performance evaluation and optimization of thermal microscope imaging systems. [ABSTRACT FROM AUTHOR]

[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 recent years, jellyfish outbreaks have frequently occurred in offshore areas worldwide, posing a significant threat to the marine fishery, tourism, coastal industry, and personal safety. Effective monitoring of jellyfish is a vital method to solve the above problems. However, the optical detection method for jellyfish is still in the primary stage. Therefore, this paper studies a jellyfish detection method based on convolution neural network theory and digital image processing technology. This paper studies the underwater image preprocessing algorithm because the quality of underwater images directly affects the detection results. The results show that the image quality is better after applying the three algorithms namely prior defogging, adaptive histogram equalization, and multi-scale retinal enhancement, which is more conducive to detection. We establish a data set containing seven species of jellyfishes and fish. A total of 2141 images are included in the data set. The YOLOv3 algorithm is used to detect jellyfish, and its feature extraction network Darknet53 is optimized to ensure it is conducted in real-time. In addition, we introduce label smoothing and cosine annealing learning rate methods during the training process. The experimental results show that the improved algorithms improve the detection accuracy of jellyfish on the premise of ensuring the detection speed. This paper lays a foundation for the construction of an underwater jellyfish optical imaging real-time monitoring system. [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]

Highlights • A new and high precision micro-scanning component design method was proposed. • A thermal microscope imaging system based on an uncooled infrared detector. • Micro-scanning technology is used in thermal microscope imaging systems to improve its spatial resolution. Abstract In order to meet the needs of subtle thermal analysis, We developed a thermal microscope imaging system based on uncooled focal plane detector in 2008. But for more sophisticated observations, the higher spatial resolution of thermal microscope imaging system is needed. Optical micro-scanning technology is one of the effective techniques to solve this problem. It can improve the systems spatial resolution based on existing imaging devices. Early we have developed an optical micro-scanning thermal microscope imaging system. But the system has a large micro-scanning error and requires high accuracy on the mechanical manufacturing and optical processing, which is not conducive to product. In order to reduce the micro-scanning error of developed optical micro-scanning thermal microscope imaging system and improve the spatial resolution of the system, a high precision micro-scanning component design method was proposed. The working principle of optical flat plate rotation micro-scanning is analyzed. The parameters and processing tolerances of micro-scanner are given. The integrated design and processing are realized with the existing uncooled thermal microscope imaging system. Results of standard oversample reconstruction for the real thermal microscope images have shown that the system is designed successfully and achieves higher resolution. It can be applied to high resolution micro-thermal analysis. [ABSTRACT FROM AUTHOR]