A night vision color image fusion method based on statistical color transform technology in YUV color space
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https://doi.org/10.54939/1859-1043.j.mst.93.2024.114-120Keywords:
Night vision; Color image fusion; Statistical color transform.Abstract
Image fusion technology combines images from different sensors into one image to fully utilize sensors, thereby improving observation efficiency and streamlining the equipment. Unlike grayscale image fusion, color image fusion assigns images from the sensors into different color channels, emphasizing the image of each sensor and enhancing the ability to detect, recognize and remember the scene. In this paper, a method of night vision color image fusion based on statistical color transform technology in YUV color space is proposed. This method transfers the color statistical parameters of a real image to the fused image and selects the optimal fusion parameters to make it more realistic and enhance infrared target visibility. The evaluation, based on color statistical parameters and human eye observation, demonstrates the effectiveness of the proposed color image fusion method.
References
[1]. N. A. Tuấn, “Tính toán thiết kế và chế tạo hệ quang trộn ảnh kết hợp khuếch đại ánh sáng yếu và ảnh nhiệt,” Tạp chí Nghiên cứu KH&CN quân sự, số Đặc san FEE, tr. 212-221, (2020).
[2]. N. A. Tuấn, “Ứng dụng thuật toán tách biên hình ảnh Canny cho thiết bị quan sát trộn ảnh quang học,” Tạp chí Nghiên cứu KH&CN quân sự, số Đặc san FEE, tr. 273-280, (2019).
[3]. T. V. Hà, “Thiết kế khối xử lý tách biên và trộn màu video ảnh nhiệt trên bộ kit Pynq-Z1 bằng Vivado HLS cho các ứng dụng trộn ảnh,” Tạp chí Nghiên cứu KH&CN quân sự, số 77, tr. 129-136, (2022).
[4]. A. Toet, et al. “New false colour mapping for image fusion.” Optical Engineering, Vol.35, No.3, pp. 650-658, (1996). DOI: https://doi.org/10.1117/1.600657
[5]. Y. F. Jiang et al. “Summary of color night vision technology.” Laser Technology, Vol.44, No.1, pp.5, (2020).
[6]. P. Philip. "Part task investigation of multispectral image fusion using gray scale and synthetic color night-vision sensor imagery for helicopter pilotage," Proceedings of SPIE - The International Society for Optical Engineering, 3062, pp.88-100, (1997).
[7]. Waxman, et al. "Color Night Vision: Opponent Processing in the Fusion of Visible and IR Imagery." Neural Networks, Vol.10, No.1, pp.1-6, (1997). DOI: https://doi.org/10.1016/S0893-6080(96)00057-3
[8]. Waxman, et al. “Solid-state color night vision: fusion of low-light visible and thermal infrared imagery.” MIT Lincoln Laboratory Journal, Vol.11, pp.41-60, (1999).
[9]. E. Reinhard, et al. “Color transfer between images.” IEEE Computer Graphics and Applications, Vol.21, No.5, pp.34-41, (2001). DOI: https://doi.org/10.1109/38.946629
[10]. A. Toet. "Natural colour mapping for multiband nightvision imagery." Information fusion, Vol.4, No.3, pp.155-166, (2003). DOI: https://doi.org/10.1016/S1566-2535(03)00038-1
[11]. Hogervorst, et al. “Method for applying daytime colors to nighttime imagery in realtime”, Proceedings of SPIE - The International Society for Optical Engineering, Bellingham, pp.697403-6974039, (2008). DOI: https://doi.org/10.1117/12.776648
[12]. Hogervorst, et al. “Fast natural color mapping for night-time imagery.” Information Fusion, Vol.11, No.2, pp. 69-77, (2010). DOI: https://doi.org/10.1016/j.inffus.2009.06.005
[13]. A. Toet, et al. “Real-Time Full Color Multiband Night Vision.” Vision Sensors and Edge Dettection, pp. 105-142, (2010). DOI: https://doi.org/10.5772/10136
[14]. A. W. Browne, et al. “Deep learning to enable color vision in the dark.” PLoS ONE, Vol.17, No. 4, pp. 1-11, (2022). DOI: https://doi.org/10.1371/journal.pone.0265185
[15]. G. Q. He, et al. "Synthesis Performance Evaluation of Multi-Sensor Image Fusion." Chinese Journal of Computers, Vol.31, No.3, pp. 486-492, (2008). DOI: https://doi.org/10.3724/SP.J.1016.2008.00486
[16]. C. Christopoulos, et al. “The JPEG2000 still image coding system: An overview.” IEEE Transactions on Consumer Electronics, Vol.46, No.4, pp. 1103-1127, (2000). DOI: https://doi.org/10.1109/30.920468
[17]. J. Liu, et al. "Visible and Infrared Thermal Image Fusion Algorithm Based on Self-Adaptive Reference Image." Spectroscopy and Spectral Analysis, Vol.36, No.12, pp.3907-3914, (2016).
[18]. L. X. Wang, et al. "Color transfer and its real-time system based on a YUV space for dual-channel video images." Transactions of Beijing Institute of Technology, Vol.27, No.3, pp.189-191, (2007).
