Abstract
Silicon-based digital cameras can record visible and near-infrared (NIR) information, in which the full color visible image (RGB) must be restored from color filter array (CFA) interpolation. In this paper, we propose a unified framework for CFA interpolation and visible/NIR image combination. To obtain a high quality color image, the traditional color interpolation from raw CFA data is improved at each pixel, which is constrained by the corresponding monochromatic NIR image in gradient difference. The experiments indicate the effectiveness of this hybrid scheme to acquire joint color and NIR information in real-time, and show that this hybrid process can generate a better color image when compared to treating interpolation and fusion separately.
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Xiaoyan Luo received her BS degree from Taiyuan University of Technology, China in 2004, and her MS and PhD degrees from Beihang University, China in 2007 and 2012, respectively. She is currently a lecturer in the Image Processing Center, School of Astronautics, Beihang University, China. Her research interests include image processing, computer vision and pattern recognition.
Jun Zhang received his BS, MS, and PhD degrees from Beihang University, China in 1987, 1991 and 2001, respectively. He is currently a professor and vice-president of Beihang University, China. His research interests lie in the areas of signal processing, integrated and heterogeneous networks, and wireless communications.
Qionghai Dai received his BS degree in mathematics from Shanxi Normal University, China in 1987, and his ME and PhD degrees in computer science and automation from Northeastern University, China in 1994 and 1996, respectively. Since 1997, he has been with the faculty of Tsinghua University, China, where he is currently a professor and the director of the Broadband Networks and Digital Media Laboratory. His research areas include signal processing, broad-band networks, video processing, and communication.
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Luo, X., Zhang, J. & Dai, Q. Hybrid fusion and interpolation algorithm with near-infrared image. Front. Comput. Sci. 9, 375–382 (2015). https://doi.org/10.1007/s11704-014-4230-3
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DOI: https://doi.org/10.1007/s11704-014-4230-3