基于相机辐射约束的大视场红外图像非均匀性校正

Feifei Xu, Xiaoxian Huang, Ying Zhou, Yutian Fu
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引用次数: 0

摘要

红外焦平面线阵探测器是实现高空间分辨率和高辐射分辨率红外成像的核心元件。由于材料不均匀导致的探测器响应率的差异以及摄像机对背景信号变化的高灵敏度,最终导致了图像的复杂非均匀性。为了有效、快速地识别目标,必须对红外相机图像进行实时非均匀性校正。最常用的方法是在每幅图像之前,基于变温黑体标定,获取每个像素点的校正系数。然而,为大视场、高分辨率的红外相机设计全光圈标定黑体难度大、成本高,可行性不高。为了校正采集图像的非均匀性,本文提出了一种基于有限约束的单场景红外图像非均匀性校正算法。该算法根据像元响应率基本不变的原则,在实验室标定得到的各探针元响应率与中心标准像元响应率之间建立约束关系,对校正系数计算中涉及的样本进行迭代筛选,从而实现图像的非均匀性校正。利用中波红外摄像机的定位成像数据对该算法进行了验证。局部均匀图像校正前的不均匀性为44.1%,校正后的不均匀性降至4.4%,而常规场景校正后的均匀性为13.5%。因此,与传统场景校正方法相比,该算法的非均匀性降低了9.13%。该算法成功突破了宽视场高分辨率红外相机无星定标装置的设计局限,提高了红外图像的目标识别效率,有利于工程实现。另外,通过测试校正30000像素*30000线的图像只需要1min左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-uniformity correction of infrared image for wide field with camera radiation constraint
Infrared focal plane linear array detector is the core element to achieve high spatial resolution and high radiometric resolution infrared imaging. Due to the difference of detector response rate caused by non-uniform materials and the high sensitivity of camera to background signal changes, the complex non-uniformity of the image is eventually caused. In order to identify targets effectively and quickly, real-time non-uniformity correction must be performed on infrared camera images. The most commonly used method is to obtain the correction coefficients of each pixel based on variable temperature blackbody calibration before each image. However, it is difficult and costly to design full-aperture calibration blackbody for infrared camera with wide field of view and high resolution, and the feasibility is not high. In order to correct the non-uniformity of the acquired image, this paper proposes a non-uniformity correction algorithm for single-scene infrared image based on finite constraints. According to the principle that the pixel response rate is basically unchanged, the algorithm establishes a constraint relationship between the response rate of each probe element obtained by laboratory calibration and the response rate of the central standard pixel to iteratively screen the samples involved in the correction coefficient calculation, so as to realize the non-uniformity correction of the image. The proposed algorithm was verified by using the location imaging data of the medium-wave infrared camera. The non-uniformity of local uniform image was 44.1% before correction, and decreased to 4.4% after correction, while the uniformity of conventional scene correction was 13.5% after correction. Therefore, the non-uniformity of the proposed algorithm is reduced by 9.13% compared with the conventional scene correction method. The algorithm successfully breaks through the design limitations of no star calibration device of the wide-field high-resolution infrared camera, improves the target recognition efficiency of infrared image, and is conducive to implement in engineer. In addition, it only takes about 1min to correct an image of 30000 pixel *30000 lines by testing.
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