在红外光谱中, 大气对不同波长辐射透过率不同, 透过率较高的波段范围称为大气窗口。 为在大视场角范围内探测目标在长波红外光谱的辐射, 弥补传统可见光相机在复杂环境下不能探测目标的缺陷, 超大视场长波红外相机应运而生。 相比于传统可见光相机, 超大视场长波红外相机覆盖视场大, 能够用于夜间、 烟雾等复杂环境, 具有一定穿透效果。 双目超大视场长波红外立体视觉系统可用于车辆夜间辅助驾驶, 军用无人化作战平台全天候信息侦察等领域。 作为实现立体视觉的第一步, 标定的准确性严重影响立体视觉中物体三维重建精度, 因此提高标定准确性是立体视觉研究中的关键问题。 标定目的是求出立体视觉成像的内部参数和外部参数, 内部参数描述相机镜头成像的物像关系, 外部参数表示两个相机之间的相对位置关系。 但超大视场长波红外相机成像畸变严重、 分辨率低、 图像对比度低, 对立体视觉标定造成极大困难。 为准确标定超大视场长波红外立体视觉外部参数, 在Scaramuzza通用相机模型基础上提出了一种基于最小二乘法的外部参数标定方法; 为评价内外参数标定结果准确性, 以常用单目角点重投影误差评价内部参数为基础, 引入外部参数, 提出一种双目角点重投影误差评价方法。 为验证方法有效性和准确性, 使用主动红外辐射标定板生成角点, 分别采用视场角（FOV）为180°和210°的两组双目超大视场长波红外相机, 在不同位置上进行标定实验。 实验结果显示, 常用的Bouguet方法双目平均重投影误差（BMRE）在0.782～0.943 pixels, 而基于最小二乘法方法BMRE处于0.620～0.754 pixels, 实验数据表明该方法有效降低了双目角点重投影误差, 提高了外部参数标定准确性。 此外, 评价方法操作简便、 客观准确, 避免在评价过程中对物点三维重建从而引入额外误差, 并且不需要高精度三维坐标测量设备。

In the infrared spectrum, the atmosphere has different transmittances for different wavelengths, and the range of the higher transmittance is called the atmospheric window. In order to detect the radiation of the target in the long-wave infrared spectrum in the large angle of view, and to make up for the defect that the conventional visible light camera cannot detect the target in a complex environment, an ultra-wide-angle long-wave infrared camera emerges. Compared with the traditional visible light camera, ultra-wide-angle long-wave infrared camera covers a large field of view and can be used in complex environments such as night-time and smoke, and has a certain penetration effect. The binocular ultra-wide-angle long-wave infrared the stereo vision can be used for vehicle night-time assisted driving, military unmanned combat platform all-weather information reconnaissance and the like. As the first step to realize the stereo vision, the accuracy of calibration seriously affects the accuracy of three-dimensional reconstruction of objects in stereo vision. Therefore, improving calibration accuracy is a key issue in stereo vision research. The purpose of calibration is to find the intrinsic parameters and extrinsic parameters of stereo vision imaging. The intrinsic parameters describe the image relationship of the camera lens imaging, and the extrinsic parameters represent the relative positional relationship between the two cameras. However, ultra-wide-angle long-wave infrared camera has severe imaging distortion, low resolution and low image contrast, which is extremely difficult for stereo vision calibration. In order to accurately calibrate the extrinsic parameters of ultra-wide-angle long-wave infrared stereo vision, this paper proposes an extrinsic parameter calibration method based on the least squares optimization based on the Scaramuzza universal camera model. Evaluate the accuracy of the intrinsic and extrinsic parameters, and the common monocular angle is used. Based on the intrinsic parameters of point projection error evaluation and introducing extrinsic parameters, a method for evaluating the binocular angle reprojection error is proposed. In order to verify the validity and accuracy of the method, the active infrared radiation calibration plate is used to generate the corner points, and two sets of binocular ultra-wide-angle long-wave infrared cameras with the field of view (FOV) of 180° and 210° are respectively used at different positions to do calibration experiments. The experimental results show that the commonly used Bouguet method has a binocular average reprojection error (BMRE) of 0.782～0.943 pixels, while the BMRE based on the least squares optimization method is at 0.620～0.754 pixels. The experimental data show that the proposed method effectively reduces the binocular angle. Projection error improves the accuracy of extrinsic parameter calibration. In addition, the evaluation method is simple, objective and accurate, avoids the three-dimensional reconstruction of the object point in the evaluation process to introduce additional errors, and does not require high-precision three-dimensional coordinate measuring equipment.