Target detection improvements using temporal integrations and spatial fusion
First Claim
1. A method to identify a potential target from image data representing a scene, comprising:
- receiving at least two frames of image data from at least one imaging sensor;
performing at least one of a pre-detection temporal fusion and a pre-detection spatial fusion of the frames of image data;
thresholding the fused image data after performing the step of performing; and
identifying candidate targets from the thresholded image data, whereinthe pre-detection temporal fusion comprises temporally integrating image data from a said imaging sensor across a plurality of time frames and the at least two frames of image data are from the sensor; and
the pre-detection spatial fusion comprises fusing the image data from a plurality of said imaging sensors across a single time frame and the at least two frames of image data include at least one frame of image data from two different sensors.
1 Assignment
0 Petitions
Accused Products
Abstract
A method for identifying potential targets as far away as possible is disclosed. In a simple background scene such as a blue sky, a target may be recognized from a relatively long distance, but for some high clutter situations such as mountains and cities, the detection range is severely reduced. The background clutter may also be non-stationary further complicating the detection of a target. To solve these problems, target detection (recognition) of the present invention is based upon temporal fusion (integration) of sensor data using pre-detection or post-detection integration techniques, instead of using the prior art technique of fusing data from only a single time frame. Also disclosed are double-thresholding and reversed-thresholding techniques which further enhance target detection and avoid the shortcomings of the traditional constant false alarm rate (CFAR) thresholding technique. The present invention further discloses improved spatial fusion techniques for target detection (recognition) employing multiple sensors instead of employing the more conventional single sensor techniques. If spatial fusion is implemented with more than three sensors, then target detection can be enhanced by also using post-detection techniques. Moreover, since the pre-detection and the post-detection technique are complementary to each other, a combination of these two integration techniques will further improve target detection (recognition) performance.
-
Citations
20 Claims
-
1. A method to identify a potential target from image data representing a scene, comprising:
-
receiving at least two frames of image data from at least one imaging sensor; performing at least one of a pre-detection temporal fusion and a pre-detection spatial fusion of the frames of image data; thresholding the fused image data after performing the step of performing; and identifying candidate targets from the thresholded image data, wherein the pre-detection temporal fusion comprises temporally integrating image data from a said imaging sensor across a plurality of time frames and the at least two frames of image data are from the sensor; and the pre-detection spatial fusion comprises fusing the image data from a plurality of said imaging sensors across a single time frame and the at least two frames of image data include at least one frame of image data from two different sensors. - View Dependent Claims (2, 3)
-
-
4. A method to identify a potential target from image data of a scene, comprising:
-
receiving at least two frames of image data from at least one imaging sensor; thresholding the frames of image data, wherein said frames of image data are frames of image data from across multiple time frames of said at least one sensor or frames of image data from a plurality of said sensors; fusing the frames of image data after thresholding, by spatial fusion if the frames of image data are frames of image data from said plurality of sensors or by temporal fusion if the frames of image data are frames of image data from across multiple time frames of said at least one sensor; and identifying candidate targets from the fused image data. - View Dependent Claims (5)
-
-
6. A device to identify potential targets from at least two frames of image data generated by at least one imaging sensor and representative of a scene, comprising:
-
a fusion module configured to perform at least one of a temporal fusion and a spatial fusion of the generated frames of image data; and a threshold module configured to apply thresholding techniques on the fused image data, wherein the temporal fusion includes temporally fusing the frames of image data across a plurality of time frames and the at least two frames of image data are from the same sensor; and the spatial fusion includes fusing the frames of image data across a single time frame and the at least two frames of image data are from different sensors. - View Dependent Claims (7, 8, 9, 10)
-
-
11. A method to identify a potential target from data, comprising the steps of:
-
receiving as input data, a plurality of time frames of data from at least one sensor; extracting, from said time frames of data, at least one feature; performing a pre-detection technique on the least one extracted feature, where said pre-detection technique includes either a double threshold technique or a reverse threshold technique; and determining whether said extracted feature is a potential target. - View Dependent Claims (12, 13, 14)
-
-
15. A method to identify a potential target from data, comprising the steps of:
-
receiving, as input, data from a plurality of sensors; performing a pre-detection fusion technique on data corresponding to at least one extracted feature from each sensor; wherein said pre-detection fusion technique includes at least one technique that is selected from a group comprised of additive fusion, multiplicative fusion, minimum fusion and maximum fusion; and determining whether the pre-detection fused data is a potential target. - View Dependent Claims (16, 17, 18)
-
-
19. A target detection apparatus, comprising:
-
a plurality of sensors for outputting data related to a target, said data from each sensor having a plurality of time frames; temporal processing means for integrating the data supplied from each of said plurality of sensors; spatial processing means for fusing the temporally integrated sensor data from said temporal processing means, wherein said spatial processing means detects the target from the spatially fused data and provides an indication corresponding to the detected target; and means for utilizing the indication of the detected target. - View Dependent Claims (20)
-
Specification