The paper presents a general paradigm of semiautomatic building extraction from aerial stereo image pair.In the semiautomatic extraction system,the building model is defined by selected roof type through human-machine...The paper presents a general paradigm of semiautomatic building extraction from aerial stereo image pair.In the semiautomatic extraction system,the building model is defined by selected roof type through human-machine interface and input the approximation of area where the extracted building exists.Then under the knowledge of the roof type,low-level and mid-level processing including edge detection,straight line segments extraction and line segments grouping are used to establish the initial geometrical model of the roof-top.However,the initial geometrical model is not so accurate in geometry.To attain accurate results,a general least squares adjustment integrating the linear templates matching model with geometrical constraints in object-space is applied to refine the initial geometrical model.The adjustment model integrating the straight edge pattern and 3D constraints together is a well-studied optimal and anti-noise method.After gaining proper initial values,this adjustment model can flexibly process extraction of kinds of roof types by changing or assembling the geometrical constraints in object-space.展开更多
In this paper, we present a simple but powerful ensemble for robust texture classification. The proposed method uses a single type of feature descriptor, i.e. scale-invariant feature transform （SIFT）, and inherits t...In this paper, we present a simple but powerful ensemble for robust texture classification. The proposed method uses a single type of feature descriptor, i.e. scale-invariant feature transform （SIFT）, and inherits the spirit of the spatial pyramid matching model （SPM）. In a flexible way of partitioning the original texture images, our approach can produce sufficient informative local features and thereby form a reliable feature pond or train a new class-specific dictionary. To take full advantage of this feature pond, we develop a group-collaboratively representation-based strategy （GCRS） for the final classification. It is solved by the well-known group lasso. But we go beyond of this and propose a locality-constraint method to speed up this, named local constraint-GCRS （LC-GCRS）. Experimental results on three public texture datasets demonstrate the proposed approach achieves competitive outcomes and even outperforms the state-of-the-art methods. Particularly, most of methods cannot work well when only a few samples of each category are available for training, but our approach still achieves very high classification accuracy, e.g. an average accuracy of 92.1% for the Brodatz dataset when only one image is used for training, significantly higher than any other methods.展开更多
Spectrally uncorrelated biphotons are the essential resources for achieving various quantum information processing protocols.We theoretically investigate the generation of spectrally uncorrelated biphotons emitted by ...Spectrally uncorrelated biphotons are the essential resources for achieving various quantum information processing protocols.We theoretically investigate the generation of spectrally uncorrelated biphotons emitted by spontaneous fourwave mixing from a fiber nonlinear interferometer which consists of an N-stage nonlinear gain fiber and an(N-1)-stage dispersion modulation fiber.The output biphoton states of nonlinear interference are the coherent superposition of various biphoton states born in each nonlinear fiber,and thus the interference fringe will reshape the biphoton joint spectra.As a result,resorting to Taylor expansion to first order for phase mismatching,we theoretically verify that the orientation of phase matching contours will rotate in a specific way with only varying the length of dispersion modulation fiber.The rotation in orientation of phase matching contours may result in spectrally uncorrelated biphotons and even arbitrary correlation biphotons.Further,we choose micro/nanofiber as the nonlinear gain fiber and single-mode communication fiber as dispersion modulation fiber to numerically simulate the generation of spectrally uncorrelated biphotons from spontaneous fourwave mixing.Here,due to significant frequency detuning(hundreds of THz),Raman background noise can be considerably suppressed,even at room temperature,and photons with largely tunable wavelengths can be achieved,indicating a practicability in many quantum fields.A photon mode purity of 97.2%will be theoretically attained without weakening the heralding nature of biphoton sources.We think that this fiber nonlinear interference with the flexibly engineered quantum state can be an excellent practical source for quantum information processing.展开更多
文摘The paper presents a general paradigm of semiautomatic building extraction from aerial stereo image pair.In the semiautomatic extraction system,the building model is defined by selected roof type through human-machine interface and input the approximation of area where the extracted building exists.Then under the knowledge of the roof type,low-level and mid-level processing including edge detection,straight line segments extraction and line segments grouping are used to establish the initial geometrical model of the roof-top.However,the initial geometrical model is not so accurate in geometry.To attain accurate results,a general least squares adjustment integrating the linear templates matching model with geometrical constraints in object-space is applied to refine the initial geometrical model.The adjustment model integrating the straight edge pattern and 3D constraints together is a well-studied optimal and anti-noise method.After gaining proper initial values,this adjustment model can flexibly process extraction of kinds of roof types by changing or assembling the geometrical constraints in object-space.
文摘In this paper, we present a simple but powerful ensemble for robust texture classification. The proposed method uses a single type of feature descriptor, i.e. scale-invariant feature transform （SIFT）, and inherits the spirit of the spatial pyramid matching model （SPM）. In a flexible way of partitioning the original texture images, our approach can produce sufficient informative local features and thereby form a reliable feature pond or train a new class-specific dictionary. To take full advantage of this feature pond, we develop a group-collaboratively representation-based strategy （GCRS） for the final classification. It is solved by the well-known group lasso. But we go beyond of this and propose a locality-constraint method to speed up this, named local constraint-GCRS （LC-GCRS）. Experimental results on three public texture datasets demonstrate the proposed approach achieves competitive outcomes and even outperforms the state-of-the-art methods. Particularly, most of methods cannot work well when only a few samples of each category are available for training, but our approach still achieves very high classification accuracy, e.g. an average accuracy of 92.1% for the Brodatz dataset when only one image is used for training, significantly higher than any other methods.
基金Project supported by the Science and Technology Key Project of Henan Province,China(Grant No.182102210577)the National Natural Science Foundation of China(Grant No.61605249)。
文摘Spectrally uncorrelated biphotons are the essential resources for achieving various quantum information processing protocols.We theoretically investigate the generation of spectrally uncorrelated biphotons emitted by spontaneous fourwave mixing from a fiber nonlinear interferometer which consists of an N-stage nonlinear gain fiber and an(N-1)-stage dispersion modulation fiber.The output biphoton states of nonlinear interference are the coherent superposition of various biphoton states born in each nonlinear fiber,and thus the interference fringe will reshape the biphoton joint spectra.As a result,resorting to Taylor expansion to first order for phase mismatching,we theoretically verify that the orientation of phase matching contours will rotate in a specific way with only varying the length of dispersion modulation fiber.The rotation in orientation of phase matching contours may result in spectrally uncorrelated biphotons and even arbitrary correlation biphotons.Further,we choose micro/nanofiber as the nonlinear gain fiber and single-mode communication fiber as dispersion modulation fiber to numerically simulate the generation of spectrally uncorrelated biphotons from spontaneous fourwave mixing.Here,due to significant frequency detuning(hundreds of THz),Raman background noise can be considerably suppressed,even at room temperature,and photons with largely tunable wavelengths can be achieved,indicating a practicability in many quantum fields.A photon mode purity of 97.2%will be theoretically attained without weakening the heralding nature of biphoton sources.We think that this fiber nonlinear interference with the flexibly engineered quantum state can be an excellent practical source for quantum information processing.
