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摘要:为了使现代制导律能够在图像制导中得以应用,提高图像制导的性能,针对图像制导难以获取目标距离信息的问题,提出基于光场成像的目标测距算法。该算法首先对光场数据进行解码和整定,从原始图像中提取出子孔径图像;其次,对两张子孔径图像进行双线性插值,以提高图像的空间分辨率;之后,选取两张子孔径图像进行标定以获取对应的内参数和外参数,并利用这些参数校正子孔径图像,使其共面且行对准;最后,采用半全局匹配方法进行图像匹配,获取目标的视差值,将视差进行三维转换即可得到目标距离。实验结果表明,改进前、后算法的平均测量误差分别为28.54 mm和14.96 mm,距离测量精度得到有效提高,能够在较为复杂的场景中有效提取目标距离信息,具有一定的理论和应用价值。Abstract:At present, it is difficult to obtain target distance information in image guidance. In order to apply modern guidance laws to image guidance technology and improve its performance, a target ranging algorithm using light field imaging is proposed. The algorithm decodes and tunes light field data to extract sub-aperture images from an original image. Bilinear interpolation is then performed on the two sub-aperture images to improve the image’s spatial resolution, and two sub-aperture images are selected as calibration data to obtain the corresponding internal and external parameters. The parameters are used to correct the sub-aperture images, which aligns them and makes them coplanar. Finally, a semi-global matching method is used to match the images to obtain the disparity value of the target. Then, 3D transformation of parallax can be used to get the target distance. The experimental results show that the average measurement errors of the algorithm are 28.54 mm and 14.96 mm, respectively, before and after improvement. This algorithm can effectively extract target distance information in complex scenes, which has value in theoretical and real-world applications.
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Key words:
- light field imaging/
- sub-aperture images/
- distance measurement
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表 1不同算法的测量结果
Table 1.Measurement results with different algorithms
距离测量/mm 有效像素点 初始算法 488.57 8051 双线性插值算法 480.59 21363 半全局匹配算法 483.10 16659 双重改进算法 466.55 57441 表 2实验结果
Table 2.Experiment results
真实距离/mm 距离测量/mm 有效像素点 时间/s A-初始算法 400 442.83 17218 1.31 A-改进算法 400 431.14 111380 6.42 B-初始算法 400 372.50 3161 1.06 B-改进算法 400 392.54 28557 5.83 C-初始算法 450 465.28 4156 1.27 C-改进算法 450 443.72 14168 5.76 -
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