水 面 高 动 态 范 围 场 景 分 焦 平 面 偏 振 成 像 的 自 适 应增 强 方 法

Objective China has vast water areas and a long coastline. Unlike sensor detection technology, imaging detection technology provides a direct display of water conditions through non-contact remote sensing images, which is of great significance for the development of water economy and water-related scientific research. In an outdoor environment, sunlight reflected on the water surface forms strong polarized glints and affects the water brightness, making it extreme challenging to obtain clear images and affecting water surface imaging. This leads to large-area pixel saturation and pixel information loss in imaging detector. Therefore, high dynamic range (HDR) imaging is required for water surface scenes. Fully utilizing polarization information can provide new insights for HDR technology in water scenes. Although glint on the water surface exhibits distinct polarization characteristics, polarized images can reduce such impacts on the rough water surface. In this study, we report a method called water surface polarization HDR (WP-HDR), which utilizes a division of focal plane (DOFP) system to suppress sunlight glints and achieve HDR imaging of water scenes. Real-time water surface HDR imaging is achieved based on the DOFP system. We hope that our basic strategy and findings can contribute to applications such as water environment protection and aquatic meteorological monitoring. Methods We focus on the polarization water surface HDR method and use the DOFP system to obtain four images in polarization directions in 0°, 45°, 90°, and 135°, respectively. Firstly, based on the principles of polarization imaging and Stokes vector calculation, we process a frame of an image from the DOFP system to obtain an image in any polarization direction. Through polarization processing, we suppress the high-intensity glints on the water surface, obtaining the maximum and minimum grayscale images simultaneously, I_max and I_min. We then use the Otsu segmentation method and filtering to segment I_max and identify the regions of interest I_dark for enhancement. Finally, we apply pixel-wise linear fusion to enhance the underexposed regions. Based on I_min and I_dark, we employ Laplacian filtering to enhance image details. The liner enhancement coefficient is determined based on the variance and mean of the dark regions targeted for enhancement. Results and Discussions We use the DOFP system to capture images for testing in three actual water scenes. The experimental results indicate that the selection of the polarization direction is consistent with theoretical analysis. The employed segmentation strategy effectively extracts dark regions. The WP-HDR and DOFP systems produce an effect that cannot be achieved with single polarization direction images, highlighting the necessity of our method and device selection. Results from real-world experiments demonstrate that bright spots in HDR images are effectively suppressed. The contour information of both background and target details becomes clearer, and the composite contrast, standard deviation, and average gradient show significant improvement. The proposed composite contrast, reflecting the degree of light suppression and the accuracy of target representation, can be increased by up to three times. The experiments confirm that our method is suitable for water surface imaging under strong reflection interference and can identify targets in aquatic environments. It also possesses advantages of scene universality, processing adaptability, and real-time handling of dynamic targets. The results are shown in Fig. 8(d). Conclusions Based on the polarization of water surface reflections, we propose an HDR imaging method called WP-HDR, which employs a DOFP system to suppress sunlight reflection in water scenes. The method utilizes the DOFP system to capture images with different polarization directions at the same moment, enabling polarization measurements of reflective water surface. The image processing involves three main steps. First, The bright spot areas in the image exhibit strong polarization characteristics. By leveraging the optimal polarization angle, minimum average grayscale, and the polarization image, the reflection on the water surface is effectively suppressed. Based on the principles of polarization imaging, we can calculate the images with the maximum and minimum grayscale, I_max and I_min. I_max features the largest interclass variance, while I_min suppresses the light. Second, applying the Otsu image segmentation and filtering on I_max, we determine the enhancement region to reduce the introduction of discrete pixels caused by reflections, accurately extracting background and targets. Third, based on image information, we apply an adaptive linear fusion to the regions requiring enhancement, enhancing the darker areas. Experimental results demonstrate that the processed images effectively suppress glints, resulting in clearer details and contour information of both the background and targets. The composite contrast, standard deviation, and average gradient show significant improvements. The proposed composite contrast reflects the degree of glare suppression and target accuracy, a potential threefold enhancement effect. The correctness and necessity of the proposed method are validated. Compared to time-domain algorithms, this method has advantages such as good real-time performance, a simplified mechanical structure, and accurate regional computation, making it more versatile and flexible. The WP-HDR method exhibits pivotal practical applications in water imaging technologies like target detection, recognition, and tracking. By utilizing polarization information, glint interference can be effectively suppressed, enhancing the effectiveness of image observations. It holds significant practical application significance for water surface environmental engineering.