In this article, a remote sensing image processing system is established to carry out the significant scientific problem that
processing and distributing the mass earth-observed data quantitatively and intelligently with high efficiency under the
Condor Environment. This system includes the submitting of the long-distantly task, the Grid middleware in the mass image processing and the quick distribution of the remote-sensing images, etc. A conclusion can be gained from the application of this system based on Grid environment. It proves to be an effective way to solve the present problem of fast processing, quick distribution and sharing of the mass remote-sensing images.
Automatic generate 3D models of buildings and other man-made structures from images has become a topic of
increasing importance, those models may be in applications such as virtual reality, entertainment industry and urban
planning. In this paper we address the main problems and available solution for the generation of 3D models from
terrestrial images. We first generate a coarse planar model of the principal scene planes and then reconstruct windows to
refine the building models. There are several points of novelty: first we reconstruct the coarse wire frame model use the
line segments matching with epipolar geometry constraint; Secondly, we detect the position of all windows in the image
and reconstruct the windows by established corner points correspondences between images, then add the windows to the
coarse model to refine the building models. The strategy is illustrated on image triple of college building.
Now, use close-range sequential images getting from ordinary digital camera to reconstruct building 3D model is becoming to a convenient, fast and economical method. In the traditional building 3D model reconstruction, always use feature points. Considering there are abundant of lines and planes on the building, a new method was carried out in this paper is that the automatic matching of line segments across images of scenes containing buildings, and the output is a 3D plane combination of the building. The system is largely line feature based, starting with line segments, matching, grouping, and proceed them to higher level features. The approach has been tested on a triplet of close-range sequential images of a common building in the campus.
3D Building modeling is the focus of the research on the theory and framework of "Digital City". The more exact of the geometrical modeling and clear of the texture mapping, the more real of the building model. In this paper, we experiment on the window, apply strict geometric constraint to match line segments across images to rapidly find out the corresponding line segments in the sequential images, reconstruct the model of windows rapidly and exactly, renew the building model vivider.
This paper describes a novel multispectral imaging microscope that can simultaneously record both spectral and spatial information of a sample, which can take advantage of spatial image processing and spectroscopic analysis techniques. A Liquid Crystal Tunable Filter device is used for fast wavelength selection and a cooled two-dimensional monochrome CCD for image detection. In order to acquire images that are not so dependent on imaging devices, a clever CCD exposure time control and a software based spectral and spatial calibration process is performed to diminish the influence of illumination, optic ununiformity, CCD’s spectral response curve and optic throughput property. A set of multispectral image processing and analysis software package is developed, which covers not only general image processing and analysis functions, and also provides powerful analysis tools for multispectral image data, including multispectral image acquisition, illumination and system response calibration, spectral analysis and etc. The combination of spatial and spectral analysis makes it an ideal tool for the applications to biomedicine. In this paper, two applications in biomedicine are also presented. One is medical image segmentation. Using multispectral imaging techniques, a mass of experiments on both marrow bone and cervical cell images showed that our segmentation results are highly satisfactory while with low computational cost. Another is biological imaging spectroscopic analysis in the study of pollen grains in rice. The results showed that the transmittance analysis of multispectral pollen images can accurately identify the pollen abortion stage of male-sterile rice, and can easily distinguish a variety of male sterile cytoplasm.
This paper describes a novel multispectral imaging microscope and its applications in the study of pollen grains in rice. The Imaging instruments can simultaneously record both spectral and spatial information of a sample, which is helpful to study the chemical states and physical properties of the sample by taking advantage of spatial image processing and spectroscopic analysis techniques. A LCTF (liquid crystal tunable filter) device is used for fast wavelength selection in the range of 400nm to 720nm and a cooled two-dimensional monochrome CCD for image detection. In this paper, the image acquisition process, spatial and spectral calibration and spectral imaging analysis methods are detailed. And also a novel method using this multispectral imaging microscope to observe rice pollen grains is reported here. The multispectral images were systematically processed and analyzed by the software. The results illustrated that the transmittance analysis of multispectral pollen images can accurately identify the pollen abortion stage of male-sterile rice, and can easily distinguish a variety of male sterile cytoplasm. Compared with cytological and histochemical methods reported previously, the method reported here has demonstrated to be more efficient and reliable in the study of chemical states and physical properties in plant cells.