In this paper, the DVRT(vector radiative transfer theory of densely distributed random discrete scatters) model to calculate the brightness temperature emitted by radiometer calibration load is presented. It takes the...
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In this paper, the DVRT(vector radiative transfer theory of densely distributed random discrete scatters) model to calculate the brightness temperature emitted by radiometer calibration load is presented. It takes the multiple scattering of isolation layer into account, which is neglected by the incoherent homogeneous model often used in calibration. Hence, it works much better than incoherent homogeneous model at millimeter wave band. Furthermore, the iteration of DVRT model is presented, and it proves that the incoherent homogeneous model is just the zero-order solution of DVRT model. Some numerical results are provided in the end.
Knowledge is one of the most important elements in production and the first resource in enterprise. By introducing knowledge to decision making, this paper presents a kind of know1edge decision- making model (KDM for ...
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Knowledge is one of the most important elements in production and the first resource in enterprise. By introducing knowledge to decision making, this paper presents a kind of know1edge decision- making model (KDM for short) based on generalized computing.
Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has...
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Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.
Motivated by the need of the numerous real-world applications, 3D object recognition has become an active research field. The representation describes the sensed data and the object models, and it is a key issue in th...
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Motivated by the need of the numerous real-world applications, 3D object recognition has become an active research field. The representation describes the sensed data and the object models, and it is a key issue in the recognition process, which decides the match strategy and the effectiveness and robustness of the recognition system. In this paper, we propose an improved 3D object representation first, which computes the local signatures of a given basis polygon on the surface mesh, and converts the signatures to a 2D array called the distance-angle (DA) images by weighted bilinear interpolation. This representation is adaptive to free-form objects and resistant to occlusion and clutter. Compared with the original representation, it has a more distinct meaning, easier operation, and adaptation to different resolutions and irregular triangle meshes. Secondly, based on the improved representation, a novel 3D recognition algorithm is presented, which has multiresolution mesh based, coarse-to-fine recognition. By matching the DA image of a polygon in the scene surface mesh with the DA images of models at low resolution, a model candidate set is obtained. The set is filtered in the neighborhood of the matched polygons in a high-resolution mesh and verified by the model candidate sets of other polygons. Experiments show that this algorithm needs less computation and is very accurate and robust.
Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In ...
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Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fur calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.
Watermarking is a technique for labeling digital pictures by hiding secret information into images. Watermark embedding is a method to discourage unauthorized copying and identify the owner or distributor of digital d...
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Watermarking is a technique for labeling digital pictures by hiding secret information into images. Watermark embedding is a method to discourage unauthorized copying and identify the owner or distributor of digital data. In this paper, a new method is proposed. The watermark is processed as a visually recognizable pattern-binary image, which includes more information than the traditional symbol or ID number and is "extracted" instead of only "detected" to characterize the owner. The watermark is hidden in the host image by selectively modifying the middle-frequency part of the host image in conjunction with the human visual system(HVS) and the image discrete cosine transform(DCT). The experimental results show that this method can survive image cropping and image compression, and get better results, this is also a prospective method.
Fast computation of three-dimensional (3-D) moments is an important and pragmatic problem. In this paper, we propose a new algorithm together with suitable systolic structure for the fast computation of 3-D moments, e...
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Fast computation of three-dimensional (3-D) moments is an important and pragmatic problem. In this paper, we propose a new algorithm together with suitable systolic structure for the fast computation of 3-D moments, extending our method for fast computation of 2-D moments. A scalable systolic structure, consisting of adders and latches, fully exploits parallelism of the network architecture and is very suitable for hardware implementation. Our new method, which also dispenses with the need for multiplication, is suitable for both binary images and gray level images. We also extend our method to efficient computation of k-dimensional (k-D) moments (k > 3).
In this paper,a parallel coordinative visual model—The revised Plate Parallel Retrieval Model(Wang 1994) [1]is presented based on the analysis of the global effect of Chinese Characters and the recent neurobiological...
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In this paper,a parallel coordinative visual model—The revised Plate Parallel Retrieval Model(Wang 1994) [1]is presented based on the analysis of the global effect of Chinese Characters and the recent neurobiological researches on the function of neuroglia in learning and *** theory assumes that visual neurons possess the function of memory and retrieval in addition to the commonly recognised function of signal *** supposes all the pixels on the array of a Chinese character are encoded,stored and relieved simultaneously and sychronously by each neuron separately.
Matching confidence is an important element for evaluating image matching quality. A method is presented which uses the technique of tests of hypotheses to determine image matching confidence under a certain testing l...
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ISBN:
(纸本)0780340531
Matching confidence is an important element for evaluating image matching quality. A method is presented which uses the technique of tests of hypotheses to determine image matching confidence under a certain testing level. The authors use similarity measurement values to be the statistics. Experimental results with large real images prove the effectiveness of the method to determine image matching confidence.
Presents an efficient method which uses two neighboring frames in image sequences for target identification. Using statistical information about the background noise and candidate regions' noise after background r...
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ISBN:
(纸本)0780342534
Presents an efficient method which uses two neighboring frames in image sequences for target identification. Using statistical information about the background noise and candidate regions' noise after background registration, we can determine those candidate regions that have the same or similar noise distributions to the background's which should be background regions, and those candidate regions that have different noise distributions from the background's which should be the target region. In particular, when there is only one target in the image, we can simply determine that the candidate region whose noise distribution is most different from the background's is the true target.
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