A new application for RBF neural networks in nonlinear mixed pixel classification for hyperspectral imaging is presented. It is a three-layer neural network with the input layer specified by spectral signatures of a m...
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A new application for RBF neural networks in nonlinear mixed pixel classification for hyperspectral imaging is presented. It is a three-layer neural network with the input layer specified by spectral signatures of a mixed pixel vector, the hidden layer used for nonlinear mixing functions and the output layer used to produce classification results of the mixed pixel vector. A noise estimation method in conjunction with noise subspace projection is developed to reliably estimate the member of mixing materials plus interference signatures that can be used as the number of hidden nodes as well as the member of input nodes. The least-mean-square learning algorithm is applied to adjust parameters used in the hidden layer and weights of the output layers adaptively and simultaneously so as to achieve best possible performance. The performance is evaluated through a series of experiments via AVIRIS data. A comparative analysis is also conducted among various methods.
The Hybrid Technology Multi-Threading project is a long-term study of the feasibility of combining several emerging technologies to reach 1 petaFLOPS within ten years. HTMT will combine high-speed superconductor proce...
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The Hybrid Technology Multi-Threading project is a long-term study of the feasibility of combining several emerging technologies to reach 1 petaFLOPS within ten years. HTMT will combine high-speed superconductor processors, semiconductor memories with built-in processors, high-speed optical interconnects, and high-density holographic storage. While there are major challenges in all aspects of this project, those in processor architecture are the focus of this paper. Fundamental differences between RSFQ circuits and conventional semiconductor circuits, including a radical jump in clock speed, make today's processor design approaches inappropriate for HTMT. Sequential instruction dispatching, even within the lowest programming unit (a strand), will lead to unacceptably high latencies, hence poor performance. We propose alternative processor designs which use fine-grain synchronizations between individual instructions in order to avoid these bottlenecks.
We present a novel method for designing polynomial FIR predictors for fixed-point environments. Our method yields filters that perform exact prediction of polynomial signals even with short coefficient word lengths. U...
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We present a novel method for designing polynomial FIR predictors for fixed-point environments. Our method yields filters that perform exact prediction of polynomial signals even with short coefficient word lengths. Under ordinary coefficient truncation or rounding, the prediction capability degrades, or may be totally lost. With the proposed method, the filters are designed so that the predictive properties are exactly preserved in fixed-point implementations. The proposed filter design method is based on integer programming (IP) and can be directly applied to any fixed-point FIR design specifications which can be formulated in a form of linear constraints on the filter coefficients.
This paper describes a 3D model-based unsupervised procedure for the segmentation of multiview image sequences using multiple sources of information. The articulation procedure is based on the homogeneity of parameter...
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This paper describes a 3D model-based unsupervised procedure for the segmentation of multiview image sequences using multiple sources of information. The articulation procedure is based on the homogeneity of parameters, such as rigid 3D motion, color and depth, estimated for each sub-object, which consists of a number of interconnected triangles of the 3D model. The rigid 3D motion of each sub-object for subsequent frames is estimated using a Kalman filtering algorithm taking into account the temporal correlation between consecutive frames. Information from all cameras is combined during the formation of the equations for the rigid 3D motion parameters. The parameter estimation for each sub-object and the 3D model segmentation procedures are interleaved and repeated iteratively until a satisfactory object segmentation emerges. The performance of the resulting segmentation method is evaluated experimentally.
The focus of this invited keynote paper (to be presented by H. J. Siegel) is mixed-machine heterogeneous computing, where a suite of different kinds of high-performance machines are interconnected by high-speed links....
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In this paper a method is presented for copyright protection in digital images. Copyright protection is achieved by embedding an invisible signal, known as digital signature or watermark, in the digital image. The met...
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In this paper a method is presented for copyright protection in digital images. Copyright protection is achieved by embedding an invisible signal, known as digital signature or watermark, in the digital image. The method proposed in this paper casts the signature in the frequency domain by slightly modifying the values of randomly selected DC coefficients of the Discrete Cosine Transform (DCT) of the image. The same method is applied also on the Subband or Wavelet Transform coefficients. An adaptive method is proposed also based on perceptual criteria that guarantees the invisibility of the watermark and avoids the deterioration of the image. Signature detection is done via hypothesis testing, without to use any information from the original image. The watermarks embedded by the proposed method are very resistant to JPEG and other frequently used compression. Experimental results using real image data verify the effectiveness of the method.
A rate-distortion framework is used to define a verv low bit rate coding scheme based on wireframe model adaptation and optimized selection of motion estima tors. This technique achieves maximum reconstructed image qu...
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A rate-distortion framework is used to define a verv low bit rate coding scheme based on wireframe model adaptation and optimized selection of motion estima tors. This technique achieves maximum reconstructed image quality under the constraint ot a target bit rate for the coding of the motion vector field, the wireframe representation information and the prediction error. Ex-perimental results illustrating the performance of the proposed techniques in very low bit rate image sequence coding application areas are presented and evaluated.
In this paper a procedure for visualisation of videocon- ference image sequences using Virtual Reality Modeling Language (VRML) 2.0 is described. First, image sequence analysis is performed in order to estimate the sh...
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In this paper a procedure for visualisation of videocon- ference image sequences using Virtual Reality Modeling Language (VRML) 2.0 is described. First, image sequence analysis is performed in order to estimate the shape and motion parameters of the person talking in front of the camera. For this purpose, we propose the K-Means with connectivity constraint algorithm as a general segmentation algorithm combining information of various types such as colour and motion. The algo-rithm is applied "hierarchically" in the image sequence and it is first used to separate the background from the foreground object and then to further segment the foreground object into the head and shoulders regions. Based on the above information, the 3D shape parameters are estimated for each sequence and a 3D model is automatically adapted. The rigid 3D motion is estimated next for each sub-object. Finally a VRML file is created containing all the above estimated information and can be viewed using any VRML 2.0 compliant browser.
In this paper a procedure for visualisation of videoconference image sequences using Virtual Reality Modeling Language (VRML) 2.0 is described. First image sequence analysis is performed in order to estimate the shape...
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A heterogeneous computing system provides a variety of different machines, orchestrated to perform an application whose subtasks have diverse execution requirements. The subtasks must be assigned to machines (matching...
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A heterogeneous computing system provides a variety of different machines, orchestrated to perform an application whose subtasks have diverse execution requirements. The subtasks must be assigned to machines (matching) and ordered for execution (scheduling) such that the overall application execution time is minimized. A new dynamic mapping (matching and scheduling) heuristic called the hybrid remapper is presented here. The hybrid remapper is based on a centralized policy and improves a statically, obtained initial matching and scheduling by remapping to reduce the overall execution time. The remapping is non-preemptive and the execution of the hybrid remapper can be overlapped with the execution of the subtasks. During application execution, the hybrid remapper uses run-time values for the subtask completion times and machine availability times whenever possible. Therefore, the hybrid remapper bases its decisions on a mixture of run-time and expected values. The potential of the hybrid remapper to improve the performance of initial static mappings is demonstrated using simulation studies.
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