Texture analysis is a fundamental field in computer vision. However,it is also a particularly difficult problem for no universal mathematical model of real world textures. By extending a new application of the fractio...Texture analysis is a fundamental field in computer vision. However,it is also a particularly difficult problem for no universal mathematical model of real world textures. By extending a new application of the fractional Fourier transform( Fr FT) in the field of texture analysis,this paper proposes an Fr FT-based method for describing textures. Firstly,based on the Radon-Wigner transform,1-D directional Fr FT filters are designed to two types of texture features,i. e.,the coarseness and directionality. Then,the frequencies with maximum and median amplitudes of the Fr FT of the input signal are regarded as the output of the 1-D directional Fr FT filter. Finally,the mean and the standard deviation are used to compose of the feature vector. Compared to the WD-based method,three benefits can be achieved with the proposed Fr FT-based method,i. e.,less memory size,lower computational load,and less disturbed by the cross-terms. The proposed method has been tested on16 standard texture images. The experimental results show that the proposed method is superior to the popular Gabor filtering-based method.展开更多
In this paper,we address the frequency estimator for 2-dimensional(2-D)complex sinusoids in the presence of white Gaussian noise.With the use of the sinc function model of the discrete Fourier transform(DFT)coefficien...In this paper,we address the frequency estimator for 2-dimensional(2-D)complex sinusoids in the presence of white Gaussian noise.With the use of the sinc function model of the discrete Fourier transform(DFT)coefficients on the input data,a fast and accurate frequency estimator is devised,where only the DFT coefficient with the highest magnitude and its four neighbors are required.Variance analysis is also included to investigate the accuracy of the proposed algorithm.Simulation results are conducted to demonstrate the superiority of the developed scheme,in terms of the estimation performance and computational complexity.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.61003128)
文摘Texture analysis is a fundamental field in computer vision. However,it is also a particularly difficult problem for no universal mathematical model of real world textures. By extending a new application of the fractional Fourier transform( Fr FT) in the field of texture analysis,this paper proposes an Fr FT-based method for describing textures. Firstly,based on the Radon-Wigner transform,1-D directional Fr FT filters are designed to two types of texture features,i. e.,the coarseness and directionality. Then,the frequencies with maximum and median amplitudes of the Fr FT of the input signal are regarded as the output of the 1-D directional Fr FT filter. Finally,the mean and the standard deviation are used to compose of the feature vector. Compared to the WD-based method,three benefits can be achieved with the proposed Fr FT-based method,i. e.,less memory size,lower computational load,and less disturbed by the cross-terms. The proposed method has been tested on16 standard texture images. The experimental results show that the proposed method is superior to the popular Gabor filtering-based method.
文摘In this paper,we address the frequency estimator for 2-dimensional(2-D)complex sinusoids in the presence of white Gaussian noise.With the use of the sinc function model of the discrete Fourier transform(DFT)coefficients on the input data,a fast and accurate frequency estimator is devised,where only the DFT coefficient with the highest magnitude and its four neighbors are required.Variance analysis is also included to investigate the accuracy of the proposed algorithm.Simulation results are conducted to demonstrate the superiority of the developed scheme,in terms of the estimation performance and computational complexity.
