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	A pupil detection method based on Unet with attention module and shape-prior loss 会议论文 OAI收割 Virtual, Online, China, 2022-12-18 作者: Song, Wenhui; Wang, Hui; Gui, Yawei; Dang, Ruochen; Hu, Bingliang \| 收藏 \| 浏览/下载：45/0 \| 提交时间：2023/03/13 pupil detection Infrared and visible light images Unet attention mechanism shape-prior loss data augmentation
	Infrared and visible image fusion based on QNSCT and Guided Filter 期刊论文 OAI收割 Optik, 2022, 卷号: 253 作者: Yang, Chenxuan; He, Yunan; Sun, Ce; Jiang, Sheng; Li, Ye \| 收藏 \| 浏览/下载：68/0 \| 提交时间：2022/02/08 Infrared and visible images Image fusion Multiscale QNSCT Guided Filter
	A line mapping based automatic registration algorithm of infrared and visible images 会议论文 OAI收割 5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013 作者: Ai R(艾锐); Shi ZL(史泽林); Xu DJ(徐德江); Zhang CS(张程硕) 收藏 \| 浏览/下载：36/0 \| 提交时间：2013/12/26 There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.
	The registration of aerial infrared and visible images (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Educational and Information Technology, ICEIT 2010, September 17, 2010 - September 19, 2010, Chongqing, China 作者: Liu J.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：23/0 \| 提交时间：2013/03/25 In order to solve the registration problem of different source image existed on aerial image fusion algorithms based on Particle Swarm Optimization (PSO) are applied as search strategy in this paper and Alignment Metric (AM) is used as judgment. This study has realized the different source image registration of infrared and visible light with high speed high accuracy and high reliability. Basically with little restriction of gray level properties a new alignment measure is applied which can efficiently measure the image registration extent and tolerate noise well. Even more the intelligent optimization algorithm - Particle Swarm Optimization (PSO) is combined to improve the registration precision and rate of infrared and visible light. Experimental results indicate that the study attains the registration accuracy of pixel level and every registration time is cut down over 40 percent compared to traditional method. The match algorithm based on AM solves the registration problem that greater differences between different source images are existed on gray and characteristic. At the same time the adoption of combining the intelligent optimization algorithms significantly improves the searching efficiency and convergence speed of the algorithms and the registration result has higher accuracy and stability which builds up solid foundation for different source image fusion. The method in this paper has a magnificent effect and is easy for application and very suitable for engineering use. 2010 IEEE.
	Fast color-transfer-based image fusion method for merging infrared and visible images (EI CONFERENCE) 会议论文 OAI收割 Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2010, April 7, 2010 - April 8, 2010, Orlando, FL, United states 作者: Xu S. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 We present a computationally efficient color image fusion algorithm for merging infrared and visible images. At the core of the proposed method is the color transfer technique based on the linear YCBCR space. The method directly uses the grayscale fused image and the difference signals of the input images to construct the source YCBCR components then uses the statistical color transfer technique to form a color fused image that takes the target image's color characteristics. Two different strategies which respectively employ the pixel averaging fusion scheme and the multiresolution fusion scheme as the grayscale image fusion solution are proposed to fulfill different user needs. The simple strategy using the pixel averaging fusion scheme answers to a need of easy implementation and speed of use. And the complex strategy using the multiresolution fusion scheme answers to the high quality need of the fused products. In addition we also describe some useful theories about color-transfer-based image fusion. Experimental results show that the proposed color image fusion algorithm can effectively produce a natural appearing "daytime-like" color fused image and even using the pixel averaging fusion scheme to implement the grayscale fusion can also provide a pleasing result. 2010 Copyright SPIE - The International Society for Optical Engineering.
	Infrared face recognition using linear subspace analysis (EI CONFERENCE) 会议论文 OAI收割 MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral Image Processing and Pattern Recognition, October 30, 2009 - November 1, 2009, Yichang, China 作者: Wang D. 收藏 \| 浏览/下载：34/0 \| 提交时间：2013/03/25 Infrared image offers the main advantage over visible image of being invariant to illumination changes for face recognition. In this paper based on the introduction of main methods of linear subspace analysis such as Principal Component Analysis (PCA) Linear Discriminant Analysis(LDA) and Fast Independent Component Analysis (FastICA) the application of these methods to the recognition of infrared face images offered by OTCBVS workshop are investigated and the advantages and disadvantages are compared. Experimental results show that the combination approach of PCA and LDA leads to better classification performance than single PCA approach or LDA approach while the FastICA approach leads to the best classification performance with the improvement of nearly 5% compared with the combination approach. 2009 Copyright SPIE - The International Society for Optical Engineering.