Designing and developement a laser imaging system with depth measurement and image defogging capabilities
Subject Areas : Journal of Radar and Optical Remote Sensing and GISAli Faraji 1 , Abbas Bashiri 2 , Mehdi Nasiri 3
1 - Master's degree student in Electrical Engineering, Electronic Warfare, Imam Hossein University, Tehran, Iran
2 - Instructor of electronic, department of Information and communication technology, Imam Hossein University, Tehran, Iran
3 - Associate Professor, Faculty of Microelectronics, Imam Hossein University, Tehran, Iran
Keywords: distance measurement in fog, stereo imaging in fog, removal of fog effects, 3D imaging,
Abstract :
Most smart and unmanned aerial vehicles use optical imagers for imaging and distance measurement. But in the foggy environment, the quality of the images taken by these systems is not good enough and there is even a possibility of destroying the images. Because the light gets scattered in contact with water vapors and fog and destroys the image recorded in the imager. Therefore, image processing is very important in these systems, but in heavy fog, distance measurement faces a serious problem. Other alternative methods are generally not economical or efficient. In this article, a new method is introduced for distance measurement and imaging on the sea surface. This method scans the environment by using two stereo imagers whose optical axis is parallel and a linear laser located on one of the cameras, and using trigonometric relations, the difference of light lines recorded in the imagers is calculated and the image and sample 3D is created from the environment. The analysis of the obtained results shows that the system is able to measure the distance of the environment with an error of less than one centimeter, and due to the type of arrangement of imagers and laser, it overcomes the effects of fog in the images with a much lower cost than other hardware.
Anwar, M. I., & Khosla, A. (2017). Vision enhancement through single image fog removal. Engineering Science and Technology, an International Journal, 20(3), 1075–1083. https://doi.org/10.1016/j.jestch.2016.11.015
John, J., & Wilscy, M. (2008). Enhancement of weather degraded video sequences using wavelet fusion. 2008 7th IEEE International Conference on Cybernetic Intelligent Systems, 1–6. https://doi.org/10.1109/UKRICIS.2008.4798926
Kokul, T., & Anparasy, S. (2020). Single Image Defogging using Depth Estimation and Scene-Specific Dark Channel Prior. 2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer), 190–195. https://doi.org/10.1109/ICTer51097.2020.9325450
Li, Z., Tan, P., Tan, R. T., Zou, D., Zhou, S. Z., & Cheong, L.-F. (2015). Simultaneous video defogging and stereo reconstruction. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4988–4997. https://doi.org/10.1109/CVPR.2015.7299133
Liu, N., Fu, Q., Guo, H., Wang, L., Tai, Y., Liu, Y., Liu, Z., Shi, H., Zhan, J., Zhang, S., & Liu, J. (2023). Multi-band polarization imaging and image processing in sea fog environment. Frontiers in Physics, 11. https://doi.org/10.3389/fphy.2023.1221472
Pizer, S. M., Amburn, E. P., Austin, J. D., Cromartie, R., Geselowitz, A., Greer, T., ter Haar Romeny, B., Zimmerman, J. B., & Zuiderveld, K. (1987). Adaptive histogram equalization and its variations. Computer Vision, Graphics, and Image Processing, 39(3), 355–368. https://doi.org/10.1016/S0734-189X(87)80186-X
Salazar-Colores, S., Moya-Sanchez, E. U., Ramos-Arreguin, J.-M., Cabal-Yepez, E., Flores, G., & Cortes, U. (2020). Fast Single Image Defogging With Robust Sky Detection. IEEE Access, 8, 149176–149189. https://doi.org/10.1109/ACCESS.2020.3015724
Xu, Y., Wen, J., Fei, L., & Zhang, Z. (2016). Review of Video and Image Defogging Algorithms and Related Studies on Image Restoration and Enhancement. IEEE Access, 4, 165–188. https://doi.org/10.1109/ACCESS.2015.2511558
Yang, Y., Bai, S., Guo, Y., & Tang, J.-B. (2013). Video Fogging Hiding Algorithm Based on Fog Theory. 2013 Ninth International Conference on Computational Intelligence and Security, 503–507. https://doi.org/10.1109/CIS.2013.112
Yoon, I., Kim, S., Kim, D., Hayes, M., & Paik, J. (2012). Adaptive defogging with color correction in the HSV color space for consumer surveillance system. IEEE Transactions on Consumer Electronics, 58(1), 111–116. https://doi.org/10.1109/TCE.2012.6170062
