Direct algorithm of wavelet transform (WT) is the numerical algorithmobtained from the integral formula of WT by directly digitization. Some problems on realizing thealgorithm are studied. Some conclusions on the dire...Direct algorithm of wavelet transform (WT) is the numerical algorithmobtained from the integral formula of WT by directly digitization. Some problems on realizing thealgorithm are studied. Some conclusions on the direct algorithm of discrete wavelet transform (DWT),such as discrete convolution operation formula of wavelet coefficients and wavelet components,sampling principle and technology to wavelets, deciding method for scale range of wavelets, measuresto solve edge effect problem, etc, are obtained. The realization of direct algorithm of continuouswavelet transform (CWT) is also studied. The computing cost of direct algorithm and Mallat algorithmof DWT are still studied, and the computing formulae are obtained. These works are beneficial todeeply understand WT and Mallat algorithm. Examples in the end show that direct algorithm can alsobe applied widely.展开更多
The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wav...The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wavelet transform coefficients and wavelet transform energy distribution constitute feature vectors. These vectors are then trained and tested using SVM multi-class algorithms. Experimental results demonstrate that the SVM multi-class algorithms, which use the Gaussian radial basis function, exponential radial basis function, and hyperbolic tangent function as basis functions, are suitable methods for power quality disturbance classification.展开更多
An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decompo...An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced.展开更多
Recently, several digital watermarking techniques have been proposed for hiding data in the frequency domain of audio signals to protect the copyrights. However, little attention has been given to the optimal position...Recently, several digital watermarking techniques have been proposed for hiding data in the frequency domain of audio signals to protect the copyrights. However, little attention has been given to the optimal position in the frequency domain for embedding watermarks. In general, there is a tradeoff between the quality of the watermarked audio and the tolerance of watermarks to signal processing methods, such as compression. In the present study, a watermarking method developed for a visual image by using a wavelet transform was applied to an audio clip. We also improved the performance of both the quality of the watermarked audio and the extraction of watermarks after compression by the MP3 technique. To accomplish this, we created a multipurpose optimization problem for deciding the positions of watermarks in the frequency domain and obtaining a near-optimum solution. The near-optimum solution is obtained by using a genetic algorithm. The experimental results show that the proposed method generates watermarked audios of good quality and high tolerance to MP3 compression. In addition, the security was improved by using the characteristic secret key to embed and extract the watermark information.展开更多
An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square er...An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.展开更多
Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presen...Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presents a new digital watermarking scheme that combines some operators of the Genetic Algorithm (GA) and the Residue Number (RN) System (RNS) to perform encryption on an image, which is embedded into a cover image for the purposes of watermarking. Thus, an image watermarking scheme uses an encrypted image. The secret image is embedded in decomposed frames of the cover image achieved by applying a three-level Discrete Wavelet Transform (DWT). This is to ensure that the secret information is not exposed even when there is a successful attack on the cover information. Content creators can prove ownership of the multimedia content by unveiling the secret information in a court of law. The proposed scheme was tested with sample data using MATLAB2022 and the results of the simulation show a great deal of imperceptibility and robustness as compared to similar existing schemes.展开更多
Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of ...Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission （AE） signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT.展开更多
The wavelet transform is a popular analysis tool for non-stationary data, but in many cases, the choice of the mother wavelet and basis set remains uncertain, particularly when dealing with physiological data. Further...The wavelet transform is a popular analysis tool for non-stationary data, but in many cases, the choice of the mother wavelet and basis set remains uncertain, particularly when dealing with physiological data. Furthermore, the possibility exists for combining information from numerous mother wavelets so as to exploit different features from the data. However, the combinatorics become daunting given the large number of basis sets that can be utilized. Recent work in evolutionary computation has produced a subset selection genetic algorithm specifically aimed at the discovery of small, high-performance, subsets from among a large pool of candidates. Our aim was to apply this algorithm to the task of locating subsets of packets from multiple mother wavelet decompositions to estimate cardiac output from chest wall motions while avoiding the computational cost of full signal reconstruction. We present experiments which show how a continuous assessment metric can be extracted from the wavelets coefficients, but the dual-objective nature of the algorithm (high accuracy with small feature sets) imposes a need to restrict the sensitivity of the continuous accuracy metric in order to achieve the small subset size desired. A possibly subtle tradeoff seems to be needed to meet the dual objectives.展开更多
In this paper, by applying a group of specific orthogonal wavelet packet to Eykho?algorithm, a new impulse response identification algorithm based on varying scale orthogonal WPTis provided. In comparison to Eykho? al...In this paper, by applying a group of specific orthogonal wavelet packet to Eykho?algorithm, a new impulse response identification algorithm based on varying scale orthogonal WPTis provided. In comparison to Eykho? algorithm, the new algorithm has better practicability andwider application range. Simulation results show that the proposed impulse response identificationalgorithm can be applied to both deterministic and random systems, and is of higher identificationprecision, stronger anti-noise interference ability and better system dynamic tracking property.展开更多
为提高月径流时间序列预测精度,改进最小二乘孪生支持向量回归机(Least Squares Twin Support Vector Regression,LSTSVR)性能,首次基于高斯核函数、多项式核函数、线性核函数构建混合核函数,提出4种季节趋势分解(Seasonal and Trend de...为提高月径流时间序列预测精度,改进最小二乘孪生支持向量回归机(Least Squares Twin Support Vector Regression,LSTSVR)性能,首次基于高斯核函数、多项式核函数、线性核函数构建混合核函数,提出4种季节趋势分解(Seasonal and Trend decomposition using Loess,STL)-小波包变换(Wavelet Packet Transform,WPT)-裂狐优化(Rüppell's Fox Optimizer,RFO)算法-混合核最小二乘孪生支持向量回归机(Hybrid Kernel Least Squares Twin Support Vector Regression,HLSTSVR)模型,并构建STL-WPT-RFO-LSTSVR、STL-WPT-RFO-混合核最小二乘支持向量回归机(Hybrid Kerllel Least Squares Twin Suppart Vector Regression,HLSSVR)、STL-WPT-RFO-最小二乘支持向量回归机(Least Squares Support Vector Regression,LSSVR)等17种对比分析模型,通过云南省高桥、凤屯水文站月径流时间序列预测实例对21种模型进行验证。首先利用STL-WPT二次分解技术对月径流序列进行分解处理,合理划分训练集和验证集;然后基于高斯核函数、多项式核函数、线性核函数,采用“三三”线性组合和“两两”线性组合的方式构建4种混合核函数对月径流分解分量进行空间映射;最后利用RFO寻优HLSTSVR/LSTSVR/HLSSVR/LSSVR最佳超参数,利用最佳超参数建立21种模型对实例月径流序列各分解分量进行训练、预测和重构。结果表明:①4种STL-WPT-RFO-HLSTSVR模型能适应不同尺度的月径流数据分布,具有较好的模型性能和较小的预测误差,其中STL-WPT-RFO-HLSTSVR(高斯+多项式+线性)模型对高桥、凤屯站月径流预测的平均绝对百分比误差MAPE分别为2.85%、2.19%,决定系数R2均为0.9994,预测精度最高、效果最好;②混合核函数兼顾了不同核函数优势,能在模型复杂度与泛化能力之间取得平衡,显著提升模型性能和预测精度;③STL-WPT二次分解技术能有效解决复杂时间序列的非平稳性、非线性和多尺度特征,较STL更具分解优势;④组合模型融合了STL-WPT、RFO和HLSTSVR优点,具有较好的普适性和参考价值。展开更多
This paper analyzes and dissertates the discrete wavelet transform and improved projection algorithm in four kernel stages （image preprocessing, license plate localization, character segmentation, license plate recog...This paper analyzes and dissertates the discrete wavelet transform and improved projection algorithm in four kernel stages （image preprocessing, license plate localization, character segmentation, license plate recognition, i.e.） of license plate recognition system in detail. At last, it gives some conclusions and suggestions on future research.展开更多
A novel algorithm for Bayesian document segmentation is proposed based on the wavelet domain hidden Markov tree (HMT) model. Once the parameters of model are known, according to the sequential maximum a posterior prob...A novel algorithm for Bayesian document segmentation is proposed based on the wavelet domain hidden Markov tree (HMT) model. Once the parameters of model are known, according to the sequential maximum a posterior probability (SMAP) rule, firstly, the likelihood probability of HMT model for each pattern is computed from fine to coarse procedure. Then, the interscale state transition probability is solved using Expectation Maximum (EM) algorithm based on hybrid-quadtree and multiscale context information is fused from coarse to fine procedure. In order to get pixel-level segmentation, the redundant wavelet domain Gaussian mixture model (GMM) is employed to formulate pixel-level statistical property. The experiment results show that the proposed scheme is feasible and robust.展开更多
In this paper, a wavelet packet feature selection method for lung sounds based on optimization is proposed to obtain the best feature set which maximizes the differences between normal lung sounds and abnormal lung so...In this paper, a wavelet packet feature selection method for lung sounds based on optimization is proposed to obtain the best feature set which maximizes the differences between normal lung sounds and abnormal lung sounds(sounds with wheezes or rales). The proposed method includes two main steps: Firstly, the wavelet packet transform(WPT) is used to extract the original features of lung sounds; then the genetic algorithm(GA) is used to select the best feature set. The obtained optimal feature set is sent to four different classifiers to evaluate the performance of the proposed method. Experimental results show that the feature set obtained by the proposed method provides a higher classification accuracy of 94.6% in comparison with the best wavelet packet basis approach and multi-scale principal component analysis(PCA) approach. Meanwhile, the proposed method has effective generalization performance and can obtain the best feature set without priori knowledge of lung sounds.展开更多
A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark,...A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark, and then the embedding and extraction of watermark are implemented in digital wavelet transform (DWT) domain. During the watermarking process, GA is employed to search optimal parameters of embedding strength and times of Arnold transform to gain the optimization of watermarking performance. Simulation results show that the proposed method can improve the quality of watermarked image and give almost the same robustness of the watermark.展开更多
Lifting scheme is a second-generation wavelet transform which is easier to understand than the first-generation wavelet transform. Fourier analysis is not necessary for the construction, and inverse transform can natu...Lifting scheme is a second-generation wavelet transform which is easier to understand than the first-generation wavelet transform. Fourier analysis is not necessary for the construction, and inverse transform can naturally be realized. Furthermore, it is faster than the first-generation wavelet transform. In terms of compression ratio and compression efficiency, SPIHT is the best algorithm based on EZW, but its theory is difficult to understand and come true. We carry out the SPIHT algorithm, and propose a reformed algorithm based on SPIHT, making the realization more easier. In the end, LSS algorithm composed of lifting scheme and SPIHT algorithm is presented, whose compression efficiency is the same as SPIHT, but running is 10% faster than SPIHT.展开更多
An efficient high precision biorthogonal 9/7 wavelet filter structure for image processing applications was proposed. This structure aimed at high precision applications. A precision improved distributed algorithms (D...An efficient high precision biorthogonal 9/7 wavelet filter structure for image processing applications was proposed. This structure aimed at high precision applications. A precision improved distributed algorithms (DA) had been proposed. Comparing with traditional DA implementations, the new DA had higher precision while preserves smaller area. The proposed structure was verified in Spartan-6 field programmable gate array (FPGA) and achieved 200 MHz operation frequency. The peak signal to noise ratio (PSNR) of reconstructed image (Lena) achieves 74 dB which is very high comparing with other implementations.展开更多
基金This project is supported by National Natural Science Foundation of China (No.50135050)
文摘Direct algorithm of wavelet transform (WT) is the numerical algorithmobtained from the integral formula of WT by directly digitization. Some problems on realizing thealgorithm are studied. Some conclusions on the direct algorithm of discrete wavelet transform (DWT),such as discrete convolution operation formula of wavelet coefficients and wavelet components,sampling principle and technology to wavelets, deciding method for scale range of wavelets, measuresto solve edge effect problem, etc, are obtained. The realization of direct algorithm of continuouswavelet transform (CWT) is also studied. The computing cost of direct algorithm and Mallat algorithmof DWT are still studied, and the computing formulae are obtained. These works are beneficial todeeply understand WT and Mallat algorithm. Examples in the end show that direct algorithm can alsobe applied widely.
文摘The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wavelet transform coefficients and wavelet transform energy distribution constitute feature vectors. These vectors are then trained and tested using SVM multi-class algorithms. Experimental results demonstrate that the SVM multi-class algorithms, which use the Gaussian radial basis function, exponential radial basis function, and hyperbolic tangent function as basis functions, are suitable methods for power quality disturbance classification.
文摘An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced.
文摘Recently, several digital watermarking techniques have been proposed for hiding data in the frequency domain of audio signals to protect the copyrights. However, little attention has been given to the optimal position in the frequency domain for embedding watermarks. In general, there is a tradeoff between the quality of the watermarked audio and the tolerance of watermarks to signal processing methods, such as compression. In the present study, a watermarking method developed for a visual image by using a wavelet transform was applied to an audio clip. We also improved the performance of both the quality of the watermarked audio and the extraction of watermarks after compression by the MP3 technique. To accomplish this, we created a multipurpose optimization problem for deciding the positions of watermarks in the frequency domain and obtaining a near-optimum solution. The near-optimum solution is obtained by using a genetic algorithm. The experimental results show that the proposed method generates watermarked audios of good quality and high tolerance to MP3 compression. In addition, the security was improved by using the characteristic secret key to embed and extract the watermark information.
基金Sponsored by the Nature Science Foundation of Jiangsu(BK2009410)
文摘An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.
文摘Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presents a new digital watermarking scheme that combines some operators of the Genetic Algorithm (GA) and the Residue Number (RN) System (RNS) to perform encryption on an image, which is embedded into a cover image for the purposes of watermarking. Thus, an image watermarking scheme uses an encrypted image. The secret image is embedded in decomposed frames of the cover image achieved by applying a three-level Discrete Wavelet Transform (DWT). This is to ensure that the secret information is not exposed even when there is a successful attack on the cover information. Content creators can prove ownership of the multimedia content by unveiling the secret information in a court of law. The proposed scheme was tested with sample data using MATLAB2022 and the results of the simulation show a great deal of imperceptibility and robustness as compared to similar existing schemes.
基金This project is supported by National Natural Science Foundation of China (No. 50105007)Program for New Century Excellent Talents in University, China.
文摘Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission （AE） signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT.
文摘The wavelet transform is a popular analysis tool for non-stationary data, but in many cases, the choice of the mother wavelet and basis set remains uncertain, particularly when dealing with physiological data. Furthermore, the possibility exists for combining information from numerous mother wavelets so as to exploit different features from the data. However, the combinatorics become daunting given the large number of basis sets that can be utilized. Recent work in evolutionary computation has produced a subset selection genetic algorithm specifically aimed at the discovery of small, high-performance, subsets from among a large pool of candidates. Our aim was to apply this algorithm to the task of locating subsets of packets from multiple mother wavelet decompositions to estimate cardiac output from chest wall motions while avoiding the computational cost of full signal reconstruction. We present experiments which show how a continuous assessment metric can be extracted from the wavelets coefficients, but the dual-objective nature of the algorithm (high accuracy with small feature sets) imposes a need to restrict the sensitivity of the continuous accuracy metric in order to achieve the small subset size desired. A possibly subtle tradeoff seems to be needed to meet the dual objectives.
文摘In this paper, by applying a group of specific orthogonal wavelet packet to Eykho?algorithm, a new impulse response identification algorithm based on varying scale orthogonal WPTis provided. In comparison to Eykho? algorithm, the new algorithm has better practicability andwider application range. Simulation results show that the proposed impulse response identificationalgorithm can be applied to both deterministic and random systems, and is of higher identificationprecision, stronger anti-noise interference ability and better system dynamic tracking property.
文摘为提高月径流时间序列预测精度,改进最小二乘孪生支持向量回归机(Least Squares Twin Support Vector Regression,LSTSVR)性能,首次基于高斯核函数、多项式核函数、线性核函数构建混合核函数,提出4种季节趋势分解(Seasonal and Trend decomposition using Loess,STL)-小波包变换(Wavelet Packet Transform,WPT)-裂狐优化(Rüppell's Fox Optimizer,RFO)算法-混合核最小二乘孪生支持向量回归机(Hybrid Kernel Least Squares Twin Support Vector Regression,HLSTSVR)模型,并构建STL-WPT-RFO-LSTSVR、STL-WPT-RFO-混合核最小二乘支持向量回归机(Hybrid Kerllel Least Squares Twin Suppart Vector Regression,HLSSVR)、STL-WPT-RFO-最小二乘支持向量回归机(Least Squares Support Vector Regression,LSSVR)等17种对比分析模型,通过云南省高桥、凤屯水文站月径流时间序列预测实例对21种模型进行验证。首先利用STL-WPT二次分解技术对月径流序列进行分解处理,合理划分训练集和验证集;然后基于高斯核函数、多项式核函数、线性核函数,采用“三三”线性组合和“两两”线性组合的方式构建4种混合核函数对月径流分解分量进行空间映射;最后利用RFO寻优HLSTSVR/LSTSVR/HLSSVR/LSSVR最佳超参数,利用最佳超参数建立21种模型对实例月径流序列各分解分量进行训练、预测和重构。结果表明:①4种STL-WPT-RFO-HLSTSVR模型能适应不同尺度的月径流数据分布,具有较好的模型性能和较小的预测误差,其中STL-WPT-RFO-HLSTSVR(高斯+多项式+线性)模型对高桥、凤屯站月径流预测的平均绝对百分比误差MAPE分别为2.85%、2.19%,决定系数R2均为0.9994,预测精度最高、效果最好;②混合核函数兼顾了不同核函数优势,能在模型复杂度与泛化能力之间取得平衡,显著提升模型性能和预测精度;③STL-WPT二次分解技术能有效解决复杂时间序列的非平稳性、非线性和多尺度特征,较STL更具分解优势;④组合模型融合了STL-WPT、RFO和HLSTSVR优点,具有较好的普适性和参考价值。
文摘This paper analyzes and dissertates the discrete wavelet transform and improved projection algorithm in four kernel stages （image preprocessing, license plate localization, character segmentation, license plate recognition, i.e.） of license plate recognition system in detail. At last, it gives some conclusions and suggestions on future research.
文摘A novel algorithm for Bayesian document segmentation is proposed based on the wavelet domain hidden Markov tree (HMT) model. Once the parameters of model are known, according to the sequential maximum a posterior probability (SMAP) rule, firstly, the likelihood probability of HMT model for each pattern is computed from fine to coarse procedure. Then, the interscale state transition probability is solved using Expectation Maximum (EM) algorithm based on hybrid-quadtree and multiscale context information is fused from coarse to fine procedure. In order to get pixel-level segmentation, the redundant wavelet domain Gaussian mixture model (GMM) is employed to formulate pixel-level statistical property. The experiment results show that the proposed scheme is feasible and robust.
基金Funded by the International Science and Technology Cooperation Foundation of Chongqing Science and Technology Commission(Grant No.cstc2012gg-gjhz0023)the 2013 Innovative Team Construction Project of Chongqing Universities
文摘In this paper, a wavelet packet feature selection method for lung sounds based on optimization is proposed to obtain the best feature set which maximizes the differences between normal lung sounds and abnormal lung sounds(sounds with wheezes or rales). The proposed method includes two main steps: Firstly, the wavelet packet transform(WPT) is used to extract the original features of lung sounds; then the genetic algorithm(GA) is used to select the best feature set. The obtained optimal feature set is sent to four different classifiers to evaluate the performance of the proposed method. Experimental results show that the feature set obtained by the proposed method provides a higher classification accuracy of 94.6% in comparison with the best wavelet packet basis approach and multi-scale principal component analysis(PCA) approach. Meanwhile, the proposed method has effective generalization performance and can obtain the best feature set without priori knowledge of lung sounds.
文摘A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark, and then the embedding and extraction of watermark are implemented in digital wavelet transform (DWT) domain. During the watermarking process, GA is employed to search optimal parameters of embedding strength and times of Arnold transform to gain the optimization of watermarking performance. Simulation results show that the proposed method can improve the quality of watermarked image and give almost the same robustness of the watermark.
文摘Lifting scheme is a second-generation wavelet transform which is easier to understand than the first-generation wavelet transform. Fourier analysis is not necessary for the construction, and inverse transform can naturally be realized. Furthermore, it is faster than the first-generation wavelet transform. In terms of compression ratio and compression efficiency, SPIHT is the best algorithm based on EZW, but its theory is difficult to understand and come true. We carry out the SPIHT algorithm, and propose a reformed algorithm based on SPIHT, making the realization more easier. In the end, LSS algorithm composed of lifting scheme and SPIHT algorithm is presented, whose compression efficiency is the same as SPIHT, but running is 10% faster than SPIHT.
文摘An efficient high precision biorthogonal 9/7 wavelet filter structure for image processing applications was proposed. This structure aimed at high precision applications. A precision improved distributed algorithms (DA) had been proposed. Comparing with traditional DA implementations, the new DA had higher precision while preserves smaller area. The proposed structure was verified in Spartan-6 field programmable gate array (FPGA) and achieved 200 MHz operation frequency. The peak signal to noise ratio (PSNR) of reconstructed image (Lena) achieves 74 dB which is very high comparing with other implementations.
