Volume 17 Issue 6
Nov.  2024
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SONG Ming-zhu, GUO Rong, LI Li-zhou, TAO Shu-ping, CHEN Yan-tong, WANG Jun-sheng. Sea surface glint suppression method based on polarization feature reconstruction[J]. Chinese Optics, 2024, 17(6): 1297-1306. doi: 10.37188/CO.2024-0008
Citation: SONG Ming-zhu, GUO Rong, LI Li-zhou, TAO Shu-ping, CHEN Yan-tong, WANG Jun-sheng. Sea surface glint suppression method based on polarization feature reconstruction[J]. Chinese Optics, 2024, 17(6): 1297-1306. doi: 10.37188/CO.2024-0008

Sea surface glint suppression method based on polarization feature reconstruction

cstr: 32171.14.CO.2024-0008
Funds:  Supported by the National Natural Science Foundation of China (No. 62205046, No. 62075219, No. 52171343); Key Technological Research Projects of Jilin Province (No. 20220201076GX); Fundamental Research Funds for the Central Universities (No. 3132023230, No. 3132023506); Dalian Youth Science and Technology Star Project (No. 2023RQ021)
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  • Corresponding author: wangjsh@dlmu.edu.cn
  • Received Date: 09 Jan 2024
  • Rev Recd Date: 25 Jan 2024
  • Accepted Date: 18 Mar 2024
  • Available Online: 17 May 2024
  • Sun 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 and feature components of linearly polarized images is proposed using the polarization characteristics of glints. We use a focal plane polarization camera to obtain four-channel linear polarized images, calculate the scene’s polarization information, and generate 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 reassigned to obtain the reconstructed glint suppression image. The glint polarization imaging experiments show that in the three sets of typical experimental data, the proportion of saturated pixels in the reconstructed glint suppressed image is decreased by up 79.07%. Compared to the intensity image, and the spatial frequency and contrast are increased by up to 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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