Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method ba...Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method based on edge features was proposed.Firstly,image edge gradient operator was introduced as a threshold based on the rule that the maximum value of the image edge gradient will decrease after the blurring process,making the blurred image be divided into two channels:edge channel and non-edge channel.Secondly,a double-channel loop iteration network was designed,where the edge gradient was used in the edge channel to sample the main edge structure and bilateral filtering was used in the non-edge channel to extract the detailed texture feature information.Finally,the feature information extracted from two channels was cyclically iterated to obtain a clear image using the deblurring model with maximum a posteriori probability.The experimental results showed that the image evaluation indexes obtained by the proposed deblurring model were superior to those of other algorithms,and the edge structure and texture details of the image were effectively recovered with better performance.展开更多
Detecting the forgery parts from a double compressed image is very important and urgent work for blind authentication. A very simple and efficient method for accomplishing the task is proposed. Firstly, the probabilis...Detecting the forgery parts from a double compressed image is very important and urgent work for blind authentication. A very simple and efficient method for accomplishing the task is proposed. Firstly, the probabilistic model with periodic effects in double quantization is analyzed, and the probability of quantized DCT coefficients in each block is calculated over the entire iraage. Secondly, the posteriori probability of each block is computed according to Bayesian theory and the results mentioned in first part. Then the mean and variance of the posteriori probability are to be used for judging whether the target block is tampered. Finally, the mathematical morphology operations are performed to reduce the false alarm probability. Experimental results show that the method can exactly locate the doctored part, and through the experiment it is also found that for detecting the tampered regions, the higher the second compression quality is, the more exact the detection efficiency is.展开更多
In this paper we propose two iterative algorithms of joint channel estimation and symbol detection for Orthogonal Frequency Division Multiplexing (OFDM) systems. In which, superimposed pilot scheme is adopted and an i...In this paper we propose two iterative algorithms of joint channel estimation and symbol detection for Orthogonal Frequency Division Multiplexing (OFDM) systems. In which, superimposed pilot scheme is adopted and an initial Channel State Information (CSI) is obtained by employing a first-order statistic. In each subsequent iteration, we propose two algorithms to update the CSI. The Mean Square Error (MSE) of channel estimation and Bit Error Rate (BER) performance are given and simulation results demonstrate that the iterative algorithm using method B has good perform-ance approaching the ideal condition.展开更多
基金supported in part by Natural Science Research Foundation of Shanxi Province(Nos.20210302123019,20210302124195,20210302124212,20210302123189)。
文摘Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method based on edge features was proposed.Firstly,image edge gradient operator was introduced as a threshold based on the rule that the maximum value of the image edge gradient will decrease after the blurring process,making the blurred image be divided into two channels:edge channel and non-edge channel.Secondly,a double-channel loop iteration network was designed,where the edge gradient was used in the edge channel to sample the main edge structure and bilateral filtering was used in the non-edge channel to extract the detailed texture feature information.Finally,the feature information extracted from two channels was cyclically iterated to obtain a clear image using the deblurring model with maximum a posteriori probability.The experimental results showed that the image evaluation indexes obtained by the proposed deblurring model were superior to those of other algorithms,and the edge structure and texture details of the image were effectively recovered with better performance.
基金supported by the National Natural Science Foundation of China(60574082)the Postdoctoral Science Foundation of China(20070421017)+2 种基金the Natural Science Foundation of Jiangsu Province(BK 2008403)the Graduate Research and Innovation Project of Jiangsu Province(CX09B-100Z)the Excellent Doctoral Dissertation Innovation Foundation of Nanjing University of Science and Technology.
文摘Detecting the forgery parts from a double compressed image is very important and urgent work for blind authentication. A very simple and efficient method for accomplishing the task is proposed. Firstly, the probabilistic model with periodic effects in double quantization is analyzed, and the probability of quantized DCT coefficients in each block is calculated over the entire iraage. Secondly, the posteriori probability of each block is computed according to Bayesian theory and the results mentioned in first part. Then the mean and variance of the posteriori probability are to be used for judging whether the target block is tampered. Finally, the mathematical morphology operations are performed to reduce the false alarm probability. Experimental results show that the method can exactly locate the doctored part, and through the experiment it is also found that for detecting the tampered regions, the higher the second compression quality is, the more exact the detection efficiency is.
基金Supported by National "863" Project (No.2002AA123031).
文摘In this paper we propose two iterative algorithms of joint channel estimation and symbol detection for Orthogonal Frequency Division Multiplexing (OFDM) systems. In which, superimposed pilot scheme is adopted and an initial Channel State Information (CSI) is obtained by employing a first-order statistic. In each subsequent iteration, we propose two algorithms to update the CSI. The Mean Square Error (MSE) of channel estimation and Bit Error Rate (BER) performance are given and simulation results demonstrate that the iterative algorithm using method B has good perform-ance approaching the ideal condition.
