COMBINING SCENE MODEL AND FUSION FOR NIGHT VIDEO ENHANCEMENT  

作　　者：Li Jing Yang Tao Pan Quan Cheng Yongmei 

机构地区：[1]School of Telecommunications Engineering, Xidian University, Xi ＇ an 710071, China [2]School of Computer Science and Engineering, Northwestern Polytechnical University, Xi＇ an 710072, China [3]School of Automation, Northwestern Polytechnical University, Xi＇an 710072, China

出　　处：《Journal of Electronics(China)》2009年第1期88-93,共6页电子科学学刊（英文版）

基　　金：Supported by the National Natural Science Foundation of China (No.60634030 and No.60372085)

摘　　要：This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminations. A unique characteristic of the algorithm is to separate the image context into two classes and estimate them in different ways. One class contains basic surrounding scene in- formation and scene model, which is obtained via background modeling and object tracking in daytime video sequence. The other class is extracted from nighttime video, including frequently moving region, high illumination region and high gradient region. The scene model and pixel-wise difference method are used to segment the three regions. A shift-invariant discrete wavelet based image fusion technique is used to integral all those context information in the final result. Experiment results demonstrate that the proposed approach can provide much more details and meaningful information for nighttime video.This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminations. A unique characteristic of the algorithm is to separate the image context into two classes and estimate them in different ways. One class contains basic surrounding scene information and scene model, which is obtained via background modeling and object tracking in daytime video sequence. The other class is extracted from nighttime video, including frequently moving region, high illumination region and high gradient region. The scene model and pixel-wise difference method are used to segment the three regions. A shift-invariant discrete wavelet based image fusion technique is used to integral all those context information in the final result. Experiment results demonstrate that the proposed approach can provide much more details and meaningful information for nighttime video.

关 键 词：Night video enhancement Image fusion Background modeling Object tracking 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]