引用本文:房卓群,于晓升,贾同,等.基于非稳态随机过程的近红外反射率鲁棒估计算法[J].控制与决策,2019,34(6):1151-1159
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基于非稳态随机过程的近红外反射率鲁棒估计算法
房卓群1, 于晓升2, 贾同1, 吴成2, 李永强1, 许茗1
(1. 东北大学信息科学与工程学院,沈阳110004;2. 东北大学机器人科学与工程学院,沈阳110004)
摘要:
反射率估计在计算机视觉、计算机图形学等领域具有重要作用.为了精确获取反射率,提出一种基于非稳态随机过程的近红外反射率鲁棒估计算法(RENA).该算法以Kinect二代传感器采集结果计算初始反射率,并建立反射率加性噪声模型,同时提出光照度鲁棒估计的概念,简化反射率图像非稳态随机过程模型.实验表明,RENA算法的反射率估计结果优于其他去噪算法,适用于室内场景的反射率图像高精度估计.
关键词:  近红外光  反射率  鲁棒估计  随机过程  深度图像  红外图像
DOI:10.13195/j.kzyjc.2017.1617
分类号:TP181
基金项目:国家自然科学基金项目(61701101, 61603080, U1613214, U1713216);国家机器人重点专项项目(2017 YFB1300900);中央高校基本科研业务费项目(N170402008, N172603001, N172604004);沈阳市科研基金项目(17-87-0-00).
Nonstationary stochastic process-based robust estimation algorithm of near-infrared albedo
FANG Zhuo-qun1,YU Xiao-sheng2,JIA Tong1,WU Cheng-dong2,LI Yong-qiang1,XU Ming1
(1. College of Information Science and Engineering,Northeastern University,Shenyang110004,China;2. Faculty of Robot Science and Engineering,Northeastern University,Shenyang 110004,China)
Abstract:
Albedo estimation plays an important role in many areas such as computer vision, computer graphics etc. A robust estimation algorithm of near-infrared albedo (RENA) based on nonstationary stochastic process is proposed in order to obtain albedo with high quality. This algorithm takes Kinect one as input and establishes an additive noise model of albedo. Simultaneously, the concept of robust shading estimation is proposed to simplify the nonstationary stochastic process model of albedo. Experiments show that estimation results of the proposed algorithm are better than other denoising algorithms, and it is suitable for high precision estimation of albedo images in indoor scenes.
Key words:  near infrared  albedo  robust estimation  stochastic process  depth image  infrared image

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