A new robust electronic image stabilization system is presented, which involves feature-point, tracking based global motion estimation and Kalman filtering based motion compensation. First, global motion is estimated ...A new robust electronic image stabilization system is presented, which involves feature-point, tracking based global motion estimation and Kalman filtering based motion compensation. First, global motion is estimated from the local motions of selected feature points. Considering the local moving objects or the inevitable mismatch, the matching validation, based on the stable relative distance between the points set is proposed, thus maintaining high accuracy and robustness. Next, the global motion parameters are accumulated for correction by Kalman filteration. The experimental result illustrates that the proposed system is effective to stabilize translational, rotational, and zooming jitter and robust to local motions.展开更多
In order to stabilize the video module to build digital image stabilization image sequence, a method of using inertial measurement system is proposed. Through applying real-time attitude in- formation of the camera th...In order to stabilize the video module to build digital image stabilization image sequence, a method of using inertial measurement system is proposed. Through applying real-time attitude in- formation of the camera that obtained by high-precision attitude sensor to estimate the image motion vector and then to compensate for image, the purpose of stabilizing the image sequence can be a- chieved. Experiments demonstrate that this method has a high image stabilization precision, and the up to 16 frame/s video output rate completely meets the real-time requirements.展开更多
Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based ...Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,respectively.For the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection curves.Then motion compensations can be obtained after using the Kalman filter method.Finally,the odd field image is adjusted according to the compensations.In the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current frame.By minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be estimated.Therefore,the even field image can be adjusted by combining the inter-field motion parameters and the odd field compensations.Finally,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field images.Experimental results show that the proposed algorithm can run in real-time and have a good stabilization performance.In addition,image blurring can be improved.展开更多
Noise,vibration and harshness(NVH)problems in vehicle engineering are always challenging in both traditional vehicles and intelligent vehicles.Although high accuracy manufacturing,modern structural roads and advanced ...Noise,vibration and harshness(NVH)problems in vehicle engineering are always challenging in both traditional vehicles and intelligent vehicles.Although high accuracy manufacturing,modern structural roads and advanced suspension technology have already significantly reduced NVH problems and their impacts;off-road condition,obstacles and extreme operating condition could still trigger NVH problems unexpectedly.This paper proposes a vehicular electronic image stabilization(EIS)system to solve the vibration problem of the camera and ensure the environment perceptive function of vehicles.Firstly,feature point detection and matching based on an oriented FAST and rotated BRIEF(ORB)algorithm are implemented to match images in the process of EIS.Furthermore,a novel improved random sampling consensus algorithm(i-RANSAC)is proposed to eliminate mismatched feature points and increase the matching accuracy significantly.And an adaptive Kalman filter(AKF)is applied to improve the adaptability of the vehicular EIS.Finally,an experimental platform based on a gasoline model car was established to validate its performance.The experimental results show that the proposed EIS system can satisfy vehicular performance requirements even under off-road condition with obvious obstacles.展开更多
A new digital image stabilization method is proposed for real-time application based on image contour. The image intensities are projected to several gray levels by thresholding before extracting contour points. Match...A new digital image stabilization method is proposed for real-time application based on image contour. The image intensities are projected to several gray levels by thresholding before extracting contour points. Matching position could be found using these contour points. All pixels are still used for refined matching near the matching position. This algorithm is more robust against changes in illumination and noise affection. The adaptive global motion judgement can remove the affection of intruding object. All those are realized on normally available PC.展开更多
A novel image stabilization system is presented,which consists of a global feature point tracking based motion estimation,a Kalman filtering based motion smoothing and an image mosaic based panoramic compensation.The ...A novel image stabilization system is presented,which consists of a global feature point tracking based motion estimation,a Kalman filtering based motion smoothing and an image mosaic based panoramic compensation.The global motion is estimated using feature point matching and iteration with the least-square method.Then,the Kalman filter is applied to smooth the original motion vectors to effectively alleviate unwanted camera vibrations and follow the intentional camera scan.Lastly,the loss information of image boundary due to the motion compensation is reconstructed with image mosaic to improve the visual quality.The experimental results show that this system can smooth unwanted translation or rotation of the video sequences and realize a panoramic stabilization at real-time speed.展开更多
An effective algorithm of electronic image stabilization (EIS) of catadioptric panoramic imaging system for track robots is presented. The key techniques of this algorithm are as follows:① A model of electronic im...An effective algorithm of electronic image stabilization (EIS) of catadioptric panoramic imaging system for track robots is presented. The key techniques of this algorithm are as follows:① A model of electronic image stabilization is built by analyzing the imaging theory and the principle of EIS, and the image shift function of unwrapped panoramic image is deduced;② The relationship equation between motion estimation parameters of annular panoramic image and motion estimation parameters of unwrapped panoramic image is developed according to the constrained aspect ratio of real objects, motion parameters of annular panoramic image are firstly estimated, and then motion parameters among the image shift function are carried out according to the relationship equation;③ An excessive stabilization threshold is presented to prevent the phenomena of excessive stabilization, and the Kalman filtering is adopted to smooth the image sequences. Numerical experimental results show that this algorithm can effectively smooth out the unwanted motion and follow the intentional camera movement under certain resolutions.展开更多
For the sake of exploring how the pattern of Chinese pine (Pinus massoniana Lamb) community changed after the invasion of the pine wood nematode (Bursaphelenchus xylophilus (Steiner & Buhrer) Niclde) in Zhousha...For the sake of exploring how the pattern of Chinese pine (Pinus massoniana Lamb) community changed after the invasion of the pine wood nematode (Bursaphelenchus xylophilus (Steiner & Buhrer) Niclde) in Zhoushan, Zhejiang Province, we established a test area in the local Chinese pine community. Landsat5 TM images from 1991 and 2006 were integrated with auxiliary data from field investigation and spectral data as additional sources of information. A method of expert knowledge classifier was applied to establish the expert knowledge dataset of the main vegetation cover types from which we obtained a forest type distribution map. The spatial patterns and stability of the forest, before and after the invasion of the pine wood nematode, were analyzed in terms of community patterns. The results indicated that the predominant coniferous forest type changed to a mixed forest. As a result, the forest structure became complex and the interaction between coniferous forest patches became weakened over the period from 1991 to 2006. Therefore, the resistance of the forest eco-system to plant diseases and insect pests and the stability of forest eco-system enhanced.展开更多
基金the National Natural Science Foundation (60572152) of China and Science Foundation ofShaanxi Province (2005F26)
文摘A new robust electronic image stabilization system is presented, which involves feature-point, tracking based global motion estimation and Kalman filtering based motion compensation. First, global motion is estimated from the local motions of selected feature points. Considering the local moving objects or the inevitable mismatch, the matching validation, based on the stable relative distance between the points set is proposed, thus maintaining high accuracy and robustness. Next, the global motion parameters are accumulated for correction by Kalman filteration. The experimental result illustrates that the proposed system is effective to stabilize translational, rotational, and zooming jitter and robust to local motions.
文摘In order to stabilize the video module to build digital image stabilization image sequence, a method of using inertial measurement system is proposed. Through applying real-time attitude in- formation of the camera that obtained by high-precision attitude sensor to estimate the image motion vector and then to compensate for image, the purpose of stabilizing the image sequence can be a- chieved. Experiments demonstrate that this method has a high image stabilization precision, and the up to 16 frame/s video output rate completely meets the real-time requirements.
基金supported by the National Natural Science Foundation of China(6110118561302145)
文摘Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,respectively.For the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection curves.Then motion compensations can be obtained after using the Kalman filter method.Finally,the odd field image is adjusted according to the compensations.In the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current frame.By minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be estimated.Therefore,the even field image can be adjusted by combining the inter-field motion parameters and the odd field compensations.Finally,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field images.Experimental results show that the proposed algorithm can run in real-time and have a good stabilization performance.In addition,image blurring can be improved.
基金National Natural Science Foundation of China(Grant Nos.52072072,52025121 and 51605087).
文摘Noise,vibration and harshness(NVH)problems in vehicle engineering are always challenging in both traditional vehicles and intelligent vehicles.Although high accuracy manufacturing,modern structural roads and advanced suspension technology have already significantly reduced NVH problems and their impacts;off-road condition,obstacles and extreme operating condition could still trigger NVH problems unexpectedly.This paper proposes a vehicular electronic image stabilization(EIS)system to solve the vibration problem of the camera and ensure the environment perceptive function of vehicles.Firstly,feature point detection and matching based on an oriented FAST and rotated BRIEF(ORB)algorithm are implemented to match images in the process of EIS.Furthermore,a novel improved random sampling consensus algorithm(i-RANSAC)is proposed to eliminate mismatched feature points and increase the matching accuracy significantly.And an adaptive Kalman filter(AKF)is applied to improve the adaptability of the vehicular EIS.Finally,an experimental platform based on a gasoline model car was established to validate its performance.The experimental results show that the proposed EIS system can satisfy vehicular performance requirements even under off-road condition with obvious obstacles.
文摘A new digital image stabilization method is proposed for real-time application based on image contour. The image intensities are projected to several gray levels by thresholding before extracting contour points. Matching position could be found using these contour points. All pixels are still used for refined matching near the matching position. This algorithm is more robust against changes in illumination and noise affection. The adaptive global motion judgement can remove the affection of intruding object. All those are realized on normally available PC.
基金supported by the National "863 Program" on High Technology Research and Development of China (Grant No.2006AA01Z127)
文摘A novel image stabilization system is presented,which consists of a global feature point tracking based motion estimation,a Kalman filtering based motion smoothing and an image mosaic based panoramic compensation.The global motion is estimated using feature point matching and iteration with the least-square method.Then,the Kalman filter is applied to smooth the original motion vectors to effectively alleviate unwanted camera vibrations and follow the intentional camera scan.Lastly,the loss information of image boundary due to the motion compensation is reconstructed with image mosaic to improve the visual quality.The experimental results show that this system can smooth unwanted translation or rotation of the video sequences and realize a panoramic stabilization at real-time speed.
基金Supported by State Key Laboratory of Explosion Science and Technology Foundation(ZDKT08-05)
文摘An effective algorithm of electronic image stabilization (EIS) of catadioptric panoramic imaging system for track robots is presented. The key techniques of this algorithm are as follows:① A model of electronic image stabilization is built by analyzing the imaging theory and the principle of EIS, and the image shift function of unwrapped panoramic image is deduced;② The relationship equation between motion estimation parameters of annular panoramic image and motion estimation parameters of unwrapped panoramic image is developed according to the constrained aspect ratio of real objects, motion parameters of annular panoramic image are firstly estimated, and then motion parameters among the image shift function are carried out according to the relationship equation;③ An excessive stabilization threshold is presented to prevent the phenomena of excessive stabilization, and the Kalman filtering is adopted to smooth the image sequences. Numerical experimental results show that this algorithm can effectively smooth out the unwanted motion and follow the intentional camera movement under certain resolutions.
文摘For the sake of exploring how the pattern of Chinese pine (Pinus massoniana Lamb) community changed after the invasion of the pine wood nematode (Bursaphelenchus xylophilus (Steiner & Buhrer) Niclde) in Zhoushan, Zhejiang Province, we established a test area in the local Chinese pine community. Landsat5 TM images from 1991 and 2006 were integrated with auxiliary data from field investigation and spectral data as additional sources of information. A method of expert knowledge classifier was applied to establish the expert knowledge dataset of the main vegetation cover types from which we obtained a forest type distribution map. The spatial patterns and stability of the forest, before and after the invasion of the pine wood nematode, were analyzed in terms of community patterns. The results indicated that the predominant coniferous forest type changed to a mixed forest. As a result, the forest structure became complex and the interaction between coniferous forest patches became weakened over the period from 1991 to 2006. Therefore, the resistance of the forest eco-system to plant diseases and insect pests and the stability of forest eco-system enhanced.