In order to overcome the phenomenon of image blur and edge loss in the process of collecting and transmitting medical image,a denoising method of medical image based on discrete wavelet transform(DWT)and modified medi...In order to overcome the phenomenon of image blur and edge loss in the process of collecting and transmitting medical image,a denoising method of medical image based on discrete wavelet transform(DWT)and modified median filter for medical image coupling denoising is proposed.The method is composed of four modules:image acquisition,image storage,image processing and image reconstruction.Image acquisition gets the medical image that contains Gaussian noise and impulse noise.Image storage includes the preservation of data and parameters of the original image and processed image.In the third module,the medical image is decomposed as four sub bands(LL,HL,LH,HH)by wavelet decomposition,where LL is low frequency,LH,HL,HH are respective for horizontal,vertical and in the diagonal line high frequency component.Using improved wavelet threshold to process high frequency coefficients and retain low frequency coefficients,the modified median filtering is performed on three high frequency sub bands after wavelet threshold processing.The last module is image reconstruction,which means getting the image after denoising by wavelet reconstruction.The advantage of this method is combining the advantages of median filter and wavelet to make the denoising effect better,not a simple combination of the two previous methods.With DWT and improved median filter coefficients coupling denoising,it is highly practical for high-precision medical images containing complex noises.The experimental results of proposed algorithm are compared with the results of median filter,wavelet transform,contourlet and DT-CWT,etc.According to visual evaluation index PSNR and SNR and Canny edge detection,in low noise images,PSNR and SNR increase by 10%–15%;in high noise images,PSNR and SNR increase by 2%–6%.The experimental results of the proposed algorithm achieved better acceptable results compared with other methods,which provides an important method for the diagnosis of medical condition.展开更多
Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband ...Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband or detail value characteristics under healthy and various faulty operating conditions. The most reliable phase current among the three phase currents was selected using an approach that employs the fuzzy entropy measure. Data were trained with a neural network system, and the fault detection algorithm was verified using the unknown data. Results of the proposed approach based on Fourier and wavelet transformations indicate that the faults can be properly classified into six categories. The training error is 5.3×10-7, and the average test error is 0.103.展开更多
The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a...The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.展开更多
Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of ...Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.展开更多
This paper proposed the reclosing method in distribution system with battery energy storage system(BESS)using wavelet transform(WT).The proposed method performs the WT of load current and then calculates the absolute ...This paper proposed the reclosing method in distribution system with battery energy storage system(BESS)using wavelet transform(WT).The proposed method performs the WT of load current and then calculates the absolute value of slope of detail coefficient.The mother wavelet used is db4of level6.The fault clearing is detected using the rapid increase of this value.After the detection of fault clearing,the reclosing is performed.To verify the proposed method,various simulations according to the fault clearing times,fault resistances,and fault lengths are performed using EMTP.The simulation results show that fault clearing can be detected using proposed absolute value of slope of detail coefficient and hence the reclosing can be performed successfully.展开更多
In order to provide larger capacity of the hidden secret data while maintaining a good visual quality of stego-image, in accordance with the visual property that human eyes are less sensitive to strong texture, a nove...In order to provide larger capacity of the hidden secret data while maintaining a good visual quality of stego-image, in accordance with the visual property that human eyes are less sensitive to strong texture, a novel steganographic method based on wavelet and modulus function is presented. First, an image is divided into blocks of prescribed size, and every block is decomposed into one-level wavelet. Then, the capacity of the hidden secret data is decided with the number of wavelet coefficients of larger magnitude. Finally, secret information is embedded by steganography based on modulus function. From the experimental results, the proposed method hides much more information and maintains a good visual quality of stego-image. Besides, the embedded data can be extracted from the stego-image without referencing the original image.展开更多
The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet d...The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm（WDIDA）, which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performanee , preserving edges and improving the visual quality of images.展开更多
In order to improve the acquisition probability of satellite navigation signals, this paper proposes a novel code acquisition method based on wavelet transform filtering. Firstly, the signal vector based on the signal...In order to improve the acquisition probability of satellite navigation signals, this paper proposes a novel code acquisition method based on wavelet transform filtering. Firstly, the signal vector based on the signal passing through a set of partial matched filters （PMFs） is built. Then, wavelet domain filtering is performed on the signal vector value. Since the correlation signal is low in frequency and narrow in bandwidth, the noise out-of-band can be filtered out and the most of the useful signal energy is retained. Thus this process greatly improves the signal to noise ratio （SNR）. Finally, the detection variable when the filtered signal goes through the combination process is constructed and the detection based on signal energy is made. Moreover, for the better retaining useful signal energy, the rule of selection of wavelet function has been made. Simulation results show the proposed method has a better detection performance than the normal code acquisition methods under the same false alarm probability.展开更多
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...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 available 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 scalable, and well suited for VLSI implementation.展开更多
In this paper, we propose a new shape-coding algorithm called wavelet-based shape coding (WBSC). Performing wavelet transform on the orientation of original planar curve gives the corners called corner-1 points and en...In this paper, we propose a new shape-coding algorithm called wavelet-based shape coding (WBSC). Performing wavelet transform on the orientation of original planar curve gives the corners called corner-1 points and end of arcs that belong to the original curve. Each arc is represented by a broken line and the corners called corner-2 points of the broken line are extracted. A polygonal approximation of a contour is an ordered list of corner-1 points, ends of arcs and corner-2 points which are extracted by using the above algorithm. All of the points are called polygonal vertices which will be compressed by our adaptive arithmetic encoding. Experimental results show that our method reduces code bits by about 26% compared with the context-based arithmetic encoding (CAE) of MPEG-4, and the subjective quality of the reconstructed shape is better than that of CAE at the same Dn.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
A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform （GWT）, a kind of energy distribution of image is obtained and checkpoints are selected according to a probability dec...A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform （GWT）, a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decision approach proposed. Then, the initialized motion vectors are obtained via a hierarcbal block-matching based on these checkpoints. Finally, by employing a 3-parameter motion model, precise parameters of global motion are found. From the experiment, the algorithm is reliable and robust.展开更多
The synchronization of two 3-scroll hyperchaotie attractors is realized based on wavelet transform and single variables＇ feedstock. In the transmitter, one signal is decomposed by wavelet transform and the detailed i...The synchronization of two 3-scroll hyperchaotie attractors is realized based on wavelet transform and single variables＇ feedstock. In the transmitter, one signal is decomposed by wavelet transform and the detailed information is removed, then the component with low frequency is reconstructed and sent into the channel In the receiver, the received signal is used as the feedback signal to realize the synchronization of two chaotic systems. Using this synchronous method, the transmitting signal is transported in compressible way, the system resource is saved, furthermore, because the transported signal is not a whole chaotic signal, the performance of security of the system is improved.展开更多
Person re-identification is a prevalent technology deployed on intelligent surveillance.There have been remarkable achievements in person re-identification methods based on the assumption that all person images have a...Person re-identification is a prevalent technology deployed on intelligent surveillance.There have been remarkable achievements in person re-identification methods based on the assumption that all person images have a sufficiently high resolution,yet such models are not applicable to the open world.In real world,the changing distance between pedestrians and the camera renders the resolution of pedestrians captured by the camera inconsistent.When low-resolution(LR)images in the query set are matched with high-resolution(HR)images in the gallery set,it degrades the performance of the pedestrian matching task due to the absent pedestrian critical information in LR images.To address the above issues,we present a dualstream coupling network with wavelet transform(DSCWT)for the cross-resolution person re-identification task.Firstly,we use the multi-resolution analysis principle of wavelet transform to separately process the low-frequency and high-frequency regions of LR images,which is applied to restore the lost detail information of LR images.Then,we devise a residual knowledge constrained loss function that transfers knowledge between the two streams of LR images and HR images for accessing pedestrian invariant features at various resolutions.Extensive qualitative and quantitative experiments across four benchmark datasets verify the superiority of the proposed approach.展开更多
A new methodology for multi-step-ahead forecasting was proposed herein which combined the wavelet transform(WT), artificial neural network(ANN) and forecasting strategies based on the changing characteristics of avail...A new methodology for multi-step-ahead forecasting was proposed herein which combined the wavelet transform(WT), artificial neural network(ANN) and forecasting strategies based on the changing characteristics of available parking spaces(APS). First, several APS time series were decomposed and reconstituted by the wavelet transform. Then, using an artificial neural network, the following five strategies for multi-step-ahead time series forecasting were used to forecast the reconstructed time series: recursive strategy, direct strategy, multi-input multi-output(MIMO) strategy, DIRMO strategy(a combination of the direct and MIMO strategies), and newly proposed recursive multi-input multi-output(RECMO) strategy which is a combination of the recursive and MIMO strategies. Finally, integrating the predicted results with the reconstructed time series produced the final forecasted available parking spaces. Three findings appear to be consistently supported by the experimental results. First, applying the wavelet transform to multi-step ahead available parking spaces forecasting can effectively improve the forecasting accuracy. Second, the forecasting resulted from the DIRMO and RECMO strategies is more accurate than that of the other strategies. Finally, the RECMO strategy requires less model training time than the DIRMO strategy and consumes the least amount of training time among five forecasting strategies.展开更多
The imaging and target detection methods for stepped frequency signal based on the wavelet transform and its power spectrum are investigated. Not only an imaging and target detection algorithm for stepped frequency si...The imaging and target detection methods for stepped frequency signal based on the wavelet transform and its power spectrum are investigated. Not only an imaging and target detection algorithm for stepped frequency signal based on the wavelet transform, but also its respective power spectrum are proposed. The multisampling property of stepped frequency signal is studied and wavelet transform is well suited for analyzing the signal. After multisampling property of stepped frequency signal being studied, it is shown that the wavelet transform is appropriate to analyze the signal. Based on the theory, the wavelet power spectrum analysis is applied to obtain the target range profile and the binary wavelet transform is used to perform target detection. To determine a suitable wavelet scaling for imaging of range profile's MMW radar, the distance resolution ΔR technique is proposed. The effectiveness of this new method is evaluated using simulated noisy radar signal. Results show that the proposed method can bring out the exactness and low computational complexity of this method.展开更多
For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data repre...For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest forms of large-scale geophysical exploration.With the identification of potential fields,we can get the map of worms or skeletonizations showing the three-dimension structure of shallow crust,and find the展开更多
For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data repre...For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest ways of large-scale geophysical exploration.With the identification of potential mineral fields,we can get the map of worms or skeletonizations showing展开更多
基金Project(2016JJ4074)supported by the Natural Science Foundation of Hunan Province,ChinaProject(14C0920)supported by the Hunan Provincial Education Department,ChinaProject(61771191)supported by the National Natural Science Foundation of China
文摘In order to overcome the phenomenon of image blur and edge loss in the process of collecting and transmitting medical image,a denoising method of medical image based on discrete wavelet transform(DWT)and modified median filter for medical image coupling denoising is proposed.The method is composed of four modules:image acquisition,image storage,image processing and image reconstruction.Image acquisition gets the medical image that contains Gaussian noise and impulse noise.Image storage includes the preservation of data and parameters of the original image and processed image.In the third module,the medical image is decomposed as four sub bands(LL,HL,LH,HH)by wavelet decomposition,where LL is low frequency,LH,HL,HH are respective for horizontal,vertical and in the diagonal line high frequency component.Using improved wavelet threshold to process high frequency coefficients and retain low frequency coefficients,the modified median filtering is performed on three high frequency sub bands after wavelet threshold processing.The last module is image reconstruction,which means getting the image after denoising by wavelet reconstruction.The advantage of this method is combining the advantages of median filter and wavelet to make the denoising effect better,not a simple combination of the two previous methods.With DWT and improved median filter coefficients coupling denoising,it is highly practical for high-precision medical images containing complex noises.The experimental results of proposed algorithm are compared with the results of median filter,wavelet transform,contourlet and DT-CWT,etc.According to visual evaluation index PSNR and SNR and Canny edge detection,in low noise images,PSNR and SNR increase by 10%–15%;in high noise images,PSNR and SNR increase by 2%–6%.The experimental results of the proposed algorithm achieved better acceptable results compared with other methods,which provides an important method for the diagnosis of medical condition.
基金Project supported by the Second Stage of Brain Korea 21 Projects
文摘Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband or detail value characteristics under healthy and various faulty operating conditions. The most reliable phase current among the three phase currents was selected using an approach that employs the fuzzy entropy measure. Data were trained with a neural network system, and the fault detection algorithm was verified using the unknown data. Results of the proposed approach based on Fourier and wavelet transformations indicate that the faults can be properly classified into six categories. The training error is 5.3×10-7, and the average test error is 0.103.
文摘The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.
基金the supported by National Natural Science Foundation of China(No.61871318 and 11574250)Scientific Research Plan Projects of Shaanxi Education Department(No.19JK0568).
文摘Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.
文摘This paper proposed the reclosing method in distribution system with battery energy storage system(BESS)using wavelet transform(WT).The proposed method performs the WT of load current and then calculates the absolute value of slope of detail coefficient.The mother wavelet used is db4of level6.The fault clearing is detected using the rapid increase of this value.After the detection of fault clearing,the reclosing is performed.To verify the proposed method,various simulations according to the fault clearing times,fault resistances,and fault lengths are performed using EMTP.The simulation results show that fault clearing can be detected using proposed absolute value of slope of detail coefficient and hence the reclosing can be performed successfully.
基金the National Natural Science Foundation of China (50677014)Hunan Provincial Natural Science Foundation of China (06JJ50114).
文摘In order to provide larger capacity of the hidden secret data while maintaining a good visual quality of stego-image, in accordance with the visual property that human eyes are less sensitive to strong texture, a novel steganographic method based on wavelet and modulus function is presented. First, an image is divided into blocks of prescribed size, and every block is decomposed into one-level wavelet. Then, the capacity of the hidden secret data is decided with the number of wavelet coefficients of larger magnitude. Finally, secret information is embedded by steganography based on modulus function. From the experimental results, the proposed method hides much more information and maintains a good visual quality of stego-image. Besides, the embedded data can be extracted from the stego-image without referencing the original image.
文摘The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm（WDIDA）, which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performanee , preserving edges and improving the visual quality of images.
基金supported by the National Natural Science Foundation of China(6117213861401340)the Fundamental Research Funds for the Central Universities(K5051302015)
文摘In order to improve the acquisition probability of satellite navigation signals, this paper proposes a novel code acquisition method based on wavelet transform filtering. Firstly, the signal vector based on the signal passing through a set of partial matched filters （PMFs） is built. Then, wavelet domain filtering is performed on the signal vector value. Since the correlation signal is low in frequency and narrow in bandwidth, the noise out-of-band can be filtered out and the most of the useful signal energy is retained. Thus this process greatly improves the signal to noise ratio （SNR）. Finally, the detection variable when the filtered signal goes through the combination process is constructed and the detection based on signal energy is made. Moreover, for the better retaining useful signal energy, the rule of selection of wavelet function has been made. Simulation results show the proposed method has a better detection performance than the normal code acquisition methods under the same false alarm probability.
文摘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 available 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 scalable, and well suited for VLSI implementation.
文摘In this paper, we propose a new shape-coding algorithm called wavelet-based shape coding (WBSC). Performing wavelet transform on the orientation of original planar curve gives the corners called corner-1 points and end of arcs that belong to the original curve. Each arc is represented by a broken line and the corners called corner-2 points of the broken line are extracted. A polygonal approximation of a contour is an ordered list of corner-1 points, ends of arcs and corner-2 points which are extracted by using the above algorithm. All of the points are called polygonal vertices which will be compressed by our adaptive arithmetic encoding. Experimental results show that our method reduces code bits by about 26% compared with the context-based arithmetic encoding (CAE) of MPEG-4, and the subjective quality of the reconstructed shape is better than that of CAE at the same Dn.
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A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform （GWT）, a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decision approach proposed. Then, the initialized motion vectors are obtained via a hierarcbal block-matching based on these checkpoints. Finally, by employing a 3-parameter motion model, precise parameters of global motion are found. From the experiment, the algorithm is reliable and robust.
文摘The synchronization of two 3-scroll hyperchaotie attractors is realized based on wavelet transform and single variables＇ feedstock. In the transmitter, one signal is decomposed by wavelet transform and the detailed information is removed, then the component with low frequency is reconstructed and sent into the channel In the receiver, the received signal is used as the feedback signal to realize the synchronization of two chaotic systems. Using this synchronous method, the transmitting signal is transported in compressible way, the system resource is saved, furthermore, because the transported signal is not a whole chaotic signal, the performance of security of the system is improved.
基金supported by the National Natural Science Foundation of China(61471154,61876057)the Key Research and Development Program of Anhui Province-Special Project of Strengthening Science and Technology Police(202004D07020012).
文摘Person re-identification is a prevalent technology deployed on intelligent surveillance.There have been remarkable achievements in person re-identification methods based on the assumption that all person images have a sufficiently high resolution,yet such models are not applicable to the open world.In real world,the changing distance between pedestrians and the camera renders the resolution of pedestrians captured by the camera inconsistent.When low-resolution(LR)images in the query set are matched with high-resolution(HR)images in the gallery set,it degrades the performance of the pedestrian matching task due to the absent pedestrian critical information in LR images.To address the above issues,we present a dualstream coupling network with wavelet transform(DSCWT)for the cross-resolution person re-identification task.Firstly,we use the multi-resolution analysis principle of wavelet transform to separately process the low-frequency and high-frequency regions of LR images,which is applied to restore the lost detail information of LR images.Then,we devise a residual knowledge constrained loss function that transfers knowledge between the two streams of LR images and HR images for accessing pedestrian invariant features at various resolutions.Extensive qualitative and quantitative experiments across four benchmark datasets verify the superiority of the proposed approach.
基金Project(51561135003)supported by the International Cooperation and Exchange of the National Natural Science Foundation of ChinaProject(51338003)supported by the Key Project of National Natural Science Foundation of China
文摘A new methodology for multi-step-ahead forecasting was proposed herein which combined the wavelet transform(WT), artificial neural network(ANN) and forecasting strategies based on the changing characteristics of available parking spaces(APS). First, several APS time series were decomposed and reconstituted by the wavelet transform. Then, using an artificial neural network, the following five strategies for multi-step-ahead time series forecasting were used to forecast the reconstructed time series: recursive strategy, direct strategy, multi-input multi-output(MIMO) strategy, DIRMO strategy(a combination of the direct and MIMO strategies), and newly proposed recursive multi-input multi-output(RECMO) strategy which is a combination of the recursive and MIMO strategies. Finally, integrating the predicted results with the reconstructed time series produced the final forecasted available parking spaces. Three findings appear to be consistently supported by the experimental results. First, applying the wavelet transform to multi-step ahead available parking spaces forecasting can effectively improve the forecasting accuracy. Second, the forecasting resulted from the DIRMO and RECMO strategies is more accurate than that of the other strategies. Finally, the RECMO strategy requires less model training time than the DIRMO strategy and consumes the least amount of training time among five forecasting strategies.
文摘The imaging and target detection methods for stepped frequency signal based on the wavelet transform and its power spectrum are investigated. Not only an imaging and target detection algorithm for stepped frequency signal based on the wavelet transform, but also its respective power spectrum are proposed. The multisampling property of stepped frequency signal is studied and wavelet transform is well suited for analyzing the signal. After multisampling property of stepped frequency signal being studied, it is shown that the wavelet transform is appropriate to analyze the signal. Based on the theory, the wavelet power spectrum analysis is applied to obtain the target range profile and the binary wavelet transform is used to perform target detection. To determine a suitable wavelet scaling for imaging of range profile's MMW radar, the distance resolution ΔR technique is proposed. The effectiveness of this new method is evaluated using simulated noisy radar signal. Results show that the proposed method can bring out the exactness and low computational complexity of this method.
文摘For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest forms of large-scale geophysical exploration.With the identification of potential fields,we can get the map of worms or skeletonizations showing the three-dimension structure of shallow crust,and find the
文摘For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest ways of large-scale geophysical exploration.With the identification of potential mineral fields,we can get the map of worms or skeletonizations showing
