Geometrically aligning two images is a basic image process in the machine vision field. In general, the geometric transformation model is selected according to the complexity of the geometric transformation between images, and the type of camera that takes the image is ignored. However, there are essential differences in the imaging mechanism between a line-scan camera and an area array camera, so the geometric transformation model of the area array image does not conform to the geometric transformation of the line-scan image. Therefore, according to the imaging model of the line-scan camera, we established the geometric transformation model of line-scan images. A line-scan image acquisition system was built, and planar objects were imaged by different line-scan camera poses. Then, taking the proposed model as the geometric transformation model, the line-scan images collected in this paper and the line-scan images of realistic application were respectively registered. As a contrast experiment, the homography of the area array image was adopted as the geometric transformation model to align these images again. Through the comparison of registration results, the correctness of the proposed geometric transformation model of line-scan images was verified, and the accuracy of the line-scan image registration was improved.

A reasonable geometric transformation model is the key to image registration. When the relative motion direction between the line-scan camera and the object is strictly parallel to the planar object, it is possible to align the image by using the eight-parameter geometric transformation model of the line-scan image. However, it will be invalid when the relative motion direction is arbitrary. Therefore, a new general geometric transformation model of line-scan images is proposed for line-scan image registration in this paper. Considering the different initial poses and motion directions of the line-scan camera, the proposed model is established based on the imaging model of the line-scan camera. In order to acquire line-scan images to verify the proposed model, a line-scan image acquisition system was built. The method based on feature points is used to register the line-scan images. The experimental results show that the proposed geometric transformation model can align the line-scan image collected under arbitrary relative motion direction, not just the parallel case. Besides, the statistical errors of the image feature point coordinates are the best performance after registration. The accuracy of the registration results is better than that of other existing geometric transformation models, which verifies the correctness and generality of the geometric transformation model of the line-scan camera proposed in this paper.

Passive polarimetric imaging has gained substantial attention over the past three decades in various applications in defense. The complexity of polarimetry modeling and measurement in the thermal infrared exceeds that of the visible and near-infrared due to the complementary polarization orientation of reflected and emitted radiance. This paper presents a comprehensive polarimetric radiance model and a degree of linear polarization (DOLP) model, both of which are specifically tailored for the infrared spectrum, accounting for both reflected and emitted radiance. Building on this foundation, we conduct an analysis and simulation of the DOLP’s variation as the object temperature changes. This analysis enables the observation of relationships that can be strategically utilized in subsequent experiments focused on measuring polarized model parameters. To mitigate the influence of reflected radiance components, the samples are subjected to high temperatures. The observed Stokes images from the sample surfaces are normalized to eliminate the dependence of each Stokes image on temperature. This parameters acquisition measurement method is particularly well-suited for refractories. Finally, the efficacy of the polarized model parameters acquisition technique is demonstrated through experiments involving three distinct refractory materials in the MWIR.