An innovative edge detection algorithm using the support value transform is presented in this *** on the support value transform, the multi scale support value images are extracted from the *** resolution of an image ...
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An innovative edge detection algorithm using the support value transform is presented in this *** on the support value transform, the multi scale support value images are extracted from the *** resolution of an image is directly related to the proper scale for edge detection, and the second level support value image is used to locate the edge positions by their zero *** experiments are carried out and sharp image edges are obtained from a variety of sample *** with many other existing methods, including LoG and Canny detectors, the proposed algorithm is superior to the LOG and Roberts approach.
The technologies of intra prediction and MBAFF were introduced, and a new intra prediction mode based on the characteristics of spatial distribution in interlaced video was proposed. The spatial correlation of five lu...
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The technologies of intra prediction and MBAFF were introduced, and a new intra prediction mode based on the characteristics of spatial distribution in interlaced video was proposed. The spatial correlation of five luma intra prediction modes in AVS-P2 and the new mode were analyzed. From the analysis result, it can be concluded that the new mode can exploit the spatial correlation better and predict the samples more precisely than the existed ones. The experimental results showed that the average gain in peak signal to noise ratio was above 0.12dB and the average reduction in bit-rate was above 1.77%, so the proposed mode is an effective prediction mode for improvement of coding performance.
A new wavelet-based image denoising algorithm, which exploits the edge information hidden in the corrupted image, is presented. Firstly, a canny-like edge detector identifies the edges in each subband. Secondly, multi...
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A new wavelet-based image denoising algorithm, which exploits the edge information hidden in the corrupted image, is presented. Firstly, a canny-like edge detector identifies the edges in each subband. Secondly, multiplying the wavelet coefficients in neighboring scales is implemented to suppress the noise while magnifying the edge information, and the result is utilized to exclude the fake edges. The isolated edge pixel is also identified as noise. Unlike the thresholding method, after that we use local window filter in the wavelet domain to remove noise in which the variance estimation is elab.rated to utilize the edge intbrmation. This method is adaptive to local image details, and can achieve bet, ter performance than the methods of state of the art.
Modelling mixtures of multivariate t-distributions are usually used instead of Gaussian mixture models(GMM) as a robust approach, when one fits a set of continuous multivariate data which have wider tail than Gaussian...
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In this paper, a registration method based on Harris corners is proposed. It is composed of three steps. First, corner extraction and matching. We use the gray level information around the corner to setup the correspo...
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Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexin...
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Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexing, as well as embedded boundary data extension technique, is adopted to optimize the design of the architecture. These reduce significantly the required numbers of the multipliers, adders and registers, as well as the amount of accessing external memory, and lead to decrease efficiently the hardware cost and power consumption of the design. The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are availab.e alternately. Experimental simulation and comparison results are presented, which demonstrate that the proposed architecture has lower hardware complexity, thus it is adapted for embedded applications. The presented architecture is simple, regular and scalab.e, and well suited for VLSI implementation.
For the 3-D reconstruction of blood vessels skeleton from biplane angiography system, an efficient 3-D reconstruction method based on neural network(NN) is proposed in this paper. First, we find a set of 2-D correspon...
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作者：
纪建田铮Department of Computer Science & Technology
Northwestern Polytechnical University Xi'an 710072 Department of Applied Mathematics
Northwestern Polytechnical UniversityXi'an 710072 Key Laboratory of Education Ministry for Image Processing and Intelligent ControlHuazhong University of Science & TechnologyWuhan 430074
The separation of noisy image is a very exciting area of research, especially when no prior information is availab.e about the noisy image. In this paper, we propose a robust independent component analysis （ICA） net...
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The separation of noisy image is a very exciting area of research, especially when no prior information is availab.e about the noisy image. In this paper, we propose a robust independent component analysis （ICA） network for separation images contaminated with high-level additive noise or outliers. We reduce the power of additive noise by adding outlier rejection rule in ICA. Extensive computer simulations confirm robustness and the excellent performance of the resulting algorithms.
Barcode has been widely applied in the modern world. This paper presents a fast and robust recognition method of noisy Code 39 barcode. The proposed method can be divided into two steps: search and decoding. In the fi...
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Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature select...
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Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature selection algorithms with artificial neural networks(ANN)usually require normalization of input data,which will probably change some characteristics of original data that are important for *** overcome the problems mentioned above,this paper combines the fuzzification layer of the neuro-fuzzy system with the multi-layer perceptron(MLP)to form a new artificial neural ***,fuzzification strategy and feature measurement based on membership space are proposed for feature selection. Finally,experiments with both natural and artificial data are carried out to compare with other methods,and the results approve the validity of the algorithm.
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