In the space surveillance applications, recognition of image targets is very important, one of the most difficult problems
in image processing is detecting objects in an image. Target detection is a key step for the applications of space image
target recognition. An improved method presented in this paper is designed to detect man-made objects in digital images
representing in natural environments. This method is based on Fractal theory. According to the fractal feature of
man-made object in space, the object can be partitioned off background based on the difference of intrinsic fractal
features between them, where the value of fractal dimension (FD) at the objects' edge is much larger than that in other
area. The validity of the proposed method is examined by processing and analyzing images of space target at the end of
the paper. In detection of targets for real images of Shenzhou-VI and launch vehicle ChangZheng(CZ), the algorithm has
a successful outcome. It will provide great efficiency and speed in detection of space image target, which could be also
used for further image feature extraction and image segmentation.
As an important part of operational effectiveness analysis of space-based system, the research on operational
effectiveness of electro-optical imaging reconnaissance satellite has great academic and realistic significance. In this
paper, we consider a certain scenario, in which a missile aided with an electro-optical imaging reconnaissance satellite
attacks a ground-based target. The operational effectiveness analysis and evaluating model of electro-optical imaging
reconnaissance satellite is built. The results of simulation demonstrate that operational effectiveness analysis and
evaluating model of electro-optical imaging reconnaissance satellite is feasible and reasonable. The models can be used
to analysis design, evaluating and development of space-based.
In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite
servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently.
Future space operations can be more economically and reliably executed using machine vision systems, which can meet
real time and tracking reliability requirements for image tracking of space surveillance system.
Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis
of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and
tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented.
The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC)
approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical
Morphology.
The validity of the proposed method is examined by processing and analyzing images of space targets. The edge
extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction
is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the
method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid
method to solve the problems of relative pose for spacecrafts.
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