In this paper,we propose a novel improved region energy based image fusion rule.The original images are firstly decomposed by using the lifting scheme of wavelet transform into four sub-bands:LL,LH,HL,HH,by studying p...In this paper,we propose a novel improved region energy based image fusion rule.The original images are firstly decomposed by using the lifting scheme of wavelet transform into four sub-bands:LL,LH,HL,HH,by studying principles and characteristics of the wavelet subbands,and we put emphasis on the high frequency subbands.Thus HH,HL,LH sub-bands,which represent three direction of high frequency details,are weighted by different size of three direction Gaussian kernel,then the energy based image fusion rule is applied with a optional size of window,thus the activity level of high frequency subbands are obtained,followed by a local region matching degree in the corresponding direction and resolution,an activity level of low frequency subband is calculated,then perform consistency verification on the selected wavelet coefficients,by doing the inverse wavelet transform the fused image is obtained.The performance of the proposed novel image fusion scheme is conducted and compared with a few existing image fusion algorithm,the experimental results show that the proposed method is an effective multi-focus image fusion algorithm.展开更多
With the development of sensor fusion technologies, there has been a lot of research on intelligent ground vehicles, where obstacle detection is one of the key aspects of vehicle driving. Obstacle detection is a compl...With the development of sensor fusion technologies, there has been a lot of research on intelligent ground vehicles, where obstacle detection is one of the key aspects of vehicle driving. Obstacle detection is a complicated task, which involves the diversity of obstacles, sensor characteristics, and environmental conditions. While the on-road driver assistance system or autonomous driving system has been well researched, the methods developed for the structured road of city scenes may fail in an off-road environment because of its uncertainty and diversity.A single type of sensor finds it hard to satisfy the needs of obstacle detection because of the sensing limitations in range, signal features, and working conditions of detection, and this motivates researchers and engineers to develop multi-sensor fusion and system integration methodology. This survey aims at summarizing the main considerations for the onboard multi-sensor configuration of intelligent ground vehicles in the off-road environments and providing users with a guideline for selecting sensors based on their performance requirements and application environments.State-of-the-art multi-sensor fusion methods and system prototypes are reviewed and associated to the corresponding heterogeneous sensor configurations. Finally, emerging technologies and challenges are discussed for future study.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.61077079)the Ph.D.Programs Foundation of Ministry of Education of China(Grant No.20102304110013)+1 种基金the Key Program of Heilongjiang Natural Science Foundation(Grant No.ZD201216)the Program ExcellentAcademic Leaders of Harbin(Grant No.RC2013XK009003)
文摘In this paper,we propose a novel improved region energy based image fusion rule.The original images are firstly decomposed by using the lifting scheme of wavelet transform into four sub-bands:LL,LH,HL,HH,by studying principles and characteristics of the wavelet subbands,and we put emphasis on the high frequency subbands.Thus HH,HL,LH sub-bands,which represent three direction of high frequency details,are weighted by different size of three direction Gaussian kernel,then the energy based image fusion rule is applied with a optional size of window,thus the activity level of high frequency subbands are obtained,followed by a local region matching degree in the corresponding direction and resolution,an activity level of low frequency subband is calculated,then perform consistency verification on the selected wavelet coefficients,by doing the inverse wavelet transform the fused image is obtained.The performance of the proposed novel image fusion scheme is conducted and compared with a few existing image fusion algorithm,the experimental results show that the proposed method is an effective multi-focus image fusion algorithm.
基金Project supported by the National Natural Science Foundation of China(Nos.61603303,61803309,and 61703343)the Natural Science Foundation of Shaanxi Province,China(No.2018JQ6070)+1 种基金the China Postdoctoral Science Foundation(No.2018M633574)the Fundamental Research Funds for the Central Universities,China(Nos.3102019ZDHKY02 and3102018JCC003)。
文摘With the development of sensor fusion technologies, there has been a lot of research on intelligent ground vehicles, where obstacle detection is one of the key aspects of vehicle driving. Obstacle detection is a complicated task, which involves the diversity of obstacles, sensor characteristics, and environmental conditions. While the on-road driver assistance system or autonomous driving system has been well researched, the methods developed for the structured road of city scenes may fail in an off-road environment because of its uncertainty and diversity.A single type of sensor finds it hard to satisfy the needs of obstacle detection because of the sensing limitations in range, signal features, and working conditions of detection, and this motivates researchers and engineers to develop multi-sensor fusion and system integration methodology. This survey aims at summarizing the main considerations for the onboard multi-sensor configuration of intelligent ground vehicles in the off-road environments and providing users with a guideline for selecting sensors based on their performance requirements and application environments.State-of-the-art multi-sensor fusion methods and system prototypes are reviewed and associated to the corresponding heterogeneous sensor configurations. Finally, emerging technologies and challenges are discussed for future study.
