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摘要:
太阳耀光是海面目标探测过程中的重要影响因素，针对陆地观测平台，利用耀光的偏振特性，提出一种基于线偏振图像共有成分与特征成分重构的海面耀光抑制方法。该方法利用分焦平面偏振相机获取四通道线偏振辐射图像，计算场景的偏振度信息，生成耀光抑制图像。在以偏振信息抑制场景耀光的基础上，结合线偏振辐射图像的特点，将耀光抑制辐射图像的光强分量分解为共有成分与特征成分，重新赋予二者新的权重因子得到重构后的耀光抑制图像。开展外场偏振实验，结果表明，针对三组典型实验数据，重构耀光抑制图像较光强图像的饱和像素占比相对降低的最大值为79.07%，空间频率与对比度相对提升的最大值分别为73.77%和172.73%。本文所提方法有效的抑制了海面场景中的耀光噪声且在背景细节信息恢复方面具有良好表现。
Abstract:Solar glint is a significant factor influencing sea surface target detection. For land observation platforms, a sea surface glint suppression method based on the reconstruction of common characteristics of linearly polarized images is proposed using the polarization characteristics of glints. The proposed method uses a focal plane polarization camera to obtain four-channel linear polarized images, calculates the scene’s polarization information, and generates a glint suppression image. Based on suppressing scene glint with polarization information combined with the characteristics of linear polarization images, the light intensity components of the glint suppression image are decomposed into common and characteristic components, and new weight factors are given to obtain the reconstructed glint suppression image. The results of field polarization experiments show that the maximum relative decrease in the proportion of saturated pixels in the reconstructed glint suppression image compared to the intensity image was 79.07%, and the maximum relative increase in spatial frequency and contrast were 73.77% and 172.73%, respectively. The method proposed in this paper effectively suppresses the glint noise in the sea scene and performs well in restoring background detail information.
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图 3 四通道线偏振光图像。（a）
${I_{{\text{0}}\text{°} }}$ 图像；（b）${I_{{\text{45}}\text{°} }}$ 图像；（c）${I_{{\text{90}}\text{°} }}$ 图像；（d）${I_{{\text{135}}\text{°} }}$ 图像Figure 3. Four-channel linearly polarized light images. (a) image
${I_{{\text{0}}\text{°} }}$ ; (b) image${I_{{\text{45}}\text{°} }}$ ; (c) image${I_{{\text{90}}\text{°} }}$ ; (d) image${I_{{\text{135}}\text{°} }}$ 
图 4 场景共有灰度成分与纹理特征成分。（a）Igray图像；（b）Itexture图像
Figure 4. Common gray component and texture feature component of scene. (a) image Igray; (b) image Itexture
图 5 强度图像及其对应的伪彩色图像。（a）（d）场景一；（b）（e）场景二；（c）（f）场景三
Figure 5. Intensity images and corresponding pseudo color images. (a) (d)scene 1; (b) (e) scene 2; (c) (f) scene 3
图 6 耀光抑制图像及其对应的伪彩色图像。（a）（d）场景一；（b）（e）场景二；（c）（f）场景三
Figure 6. Glint suppression images and corresponding pseudo color images. (a) (d)scene 1; (b) (e) scene 2; (c) (f) scene 3
图 7 重构耀光抑制图像及其对应的伪彩色图像。（a）（d）场景一；（b）（e）场景二；（c）（f）场景三
Figure 7. Reconstructed glint suppression images and corresponding pseudo color images. (a) (d) scene 1; (b) (e) scene 2; (c) (f) scene 3
图 9 耀光抑制前后，图像空间频率及对比度随曝光时间的变化情况。（a）空间频率；（b）对比度
Figure 9. The alteration of image spatial frequency and contrast in relation to exposure time before and after glint suppression. (a) spatial frequency; (b) contrast
表 1 线偏振图像评价指标
Table 1. Linearly polarized image evaluation index
评价指标 ${I_{{\text{0}}\text{°} }}$ ${I_{45\text{°} }}$ ${I_{{\text{90}}\text{°} }}$ ${I_{135\text{°} }}$ 空间频率 42.33 39.87 30.94 43.69 对比度 0.48 0.39 0.37 0.35 
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表 2 图像的评价指标
Table 2. Image quality evaluation index
实验区域 评价指标 $ I $ $ t_{f} $ $ I_{\mathrm{tt}} $ 文献[16] 文献[17] 场景1 饱和像素占比/% 48.55 20.71 10.16 14.04 11.12 空间频率 32.12 39.45 45.29 39.57 42.57 对比度 0.39 0.51 0.54 0.47 0.47 场景2 饱和像素占比/% 59.79 24.92 14.91 41.62 18.57 空间频率 17.69 26.87 30.74 19.26 21.45 对比度 0.11 0.26 0.30 0.10 0.17 场景3 饱和像素占比/% 31.07 24.72 22.33 25.49 22.49 空间频率 33.10 38.29 46.37 34.94 32.12 对比度 — — — — —
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