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摘要:
针对火星探测器着陆时沙尘天气对机器视觉的影响,提出一种去除沙尘天气对光学成像影响的方法,为视觉系统提供清晰输入图像。首先对受沙尘天气影响的图像建立模型,然后求取模型中大气光值与透射系数值。对于大气光值的计算采用基于四叉树细分的方法,在最小值图像上搜寻指定阈值面积中灰度均值最大的区域,在初始图像中相同区域计算各通道均值,作为大气光值。在此基础上计算透射系数,完成清晰图像的恢复。通过对受沙尘影响图像测试表明,该方法能够将受沙尘影响的图像恢复成清晰的图像。即使在复杂的环境中,该方法对光照变化、沙尘强度变化和场景变化等仍具有较好的效果。与其他方法相比,本文方法在去除沙尘对光学图像影响方面效果较好,在恢复图像评价指标等方面优于其他方法,能够进一步提高图像清晰度,为光学图像的后期处理提供更丰富信息。
Abstract:For dust impact on machine vision of the probe landing in Mars, a method was brought forward to remove the effect of dust on optical image and provide clear input image for the visual system. First, a model was built for the dust image. Then, the values of the atmospheric light and the transmission coefficient of the model were obtained by calculation. Among them, a quadtree subdivision approach was employed to calculate the value of the atmospheric light. The computing method was to search the maximal average region of the specified threshold area on the minimum image. Then the mean values of each channel on the same position of the original image were calculated as the estimation value of atmosphere light. And on this basis, the calculation of transmission coefficient was performed. At last, the recovery of the clear picture was finished. Test on dust images indicates that the dust image can be restored to clear image by the proposed method. Even in the complex environment, this method has high robustness to illumination variations, dust intensity change and scene change. Compared to other methods, this method has better effect in removing dust impact on optical images and is superior to other methods in terms of the restoring image evaluation index. It can further improve the clearness of dust images and provide more abundant information for post-processing.
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Key words:
- image enhancement /
- dust environment /
- quadtree /
- atmospheric light estimation /
- Mars
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表 1 定量分析对比
Table 1. Comparison of quantitative analysis
客观评价指标 初始图像 MSR SSR MSRCR 本文方法 清晰度 3.0222 6.5353 6.5319 6.5368 12.2851 标准差 12.4507 25.6661 25.7078 25.1149 38.3383 表 2 边缘强度对比
Table 2. Comparison of edge intensity
客观评价指标 初始图像 MSR SSR MSRCR 本文方法 边缘强度 24.3585 51.88445 51.8465 51.7509 96.1843 -
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