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
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
Discrete wavelet transform(DWT)algorithm is an encryption algorithm based on wavelet transform for frequency decomposition of signals or images on multiple scales.Based on the Loongson 2K processor platform,the audio,...Discrete wavelet transform(DWT)algorithm is an encryption algorithm based on wavelet transform for frequency decomposition of signals or images on multiple scales.Based on the Loongson 2K processor platform,the audio,picture and video information as carriers to encrypt and decrypt the watermark information is realized by integrating and stacking the watermark detection functions on the processor platform of the switching nodes in the off-chain communication network within blockchain systems,using the sliding window mechanism of Loongson 2K to control the smoothness of the digital information,and by multi-thread mechanism of the processor to control the real-time performance of the digital signal transmission.The performance of the least significant bit(LSB)algorithm,discrete cosine transform(DCT)algorithm,and DWT algorithm is analyzed.The performance comparison of LSB algorithm,DCT algorithm,and DWT algorithm under filtering attack,scaling attack,noise attack,cropping attack,and spin attack is simulated respectively.The experimental results show that,filtered attack normalized correlation(NC)coefficient for DWT is 0.95786,for scaled attack is 0.98962,for noise attack is 0.93842,spin attack NC is 0.86823,and clipped attack NC is 0.878814.The DWT algorithm has the small image distortion rate,is more robust to audio and video watermarking against attack effects,and the experimental data are superior to the LSB and DCT algorithms.Using Loongson 2K multi-threading mode to control the real-time data transmission,greatly improves the practicability of DWT algorithm on embedded devices,which can be effectively applied to authenticity verification when media data such as images and audio are uploaded to the blockchain.展开更多
In this paper,shortcoming of traditional wavelet denoising in real-time signal processing is discussed,requirements of online denoising are considered,and a moving window is introduced into traditional wavelet transfo...In this paper,shortcoming of traditional wavelet denoising in real-time signal processing is discussed,requirements of online denoising are considered,and a moving window is introduced into traditional wavelet transform.Using the moving window,an online wavelet denoising approach is proposed.Some problems of online denoising,such as border distortion and pseudo-Gibbs phenomena,are discussed.To solve these problems,window extension and window cycle spinning are also proposed.Different approaches are tested by the signal widely used in denoising domain.Both the visual results and the quantitative measures are presented to highlight the availability of the new approach.展开更多
For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background mod...For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background model kept a sample of intensity values for each pixel in the image and used this sample to estimate the probability density function of the pixel intensity. The density function was estimated using a new Marr wavelet kernel density estimation technique. Since this approach was quite general, the model could approximate any distribution for the pixel intensity without any assumptions about the underlying distribution shape. The background and current frame were transformed in the binary discrete wavelet domain, and background subtraction was performed in each sub-band. After obtaining the foreground, shadow was eliminated by an edge detection method. Experimental results show that the proposed method produces good results with much lower computational complexity and effectively extracts the moving objects with accuracy ratio higher than 90%, indicating that the proposed method is an effective algorithm for intelligent transportation system.展开更多
The onset times of acoustic signals with spikes,heavy bodies and unclear takeoffs are difficult to be picked accurately by the automatic method at present.To deal with this problem,an improved joint method based on th...The onset times of acoustic signals with spikes,heavy bodies and unclear takeoffs are difficult to be picked accurately by the automatic method at present.To deal with this problem,an improved joint method based on the discrete wavelet transform(DWT),modified energy ratio(MER)and Akaike information criterion(AIC)pickers,has been proposed in this study.First,the DWT is used to decompose the signal into various components.Then,the joint application of MER and AIC pickers is carried out to pick the initial onset times of all selected components,where the minimum AIC position ahead of MER onset time is regarded as the initial onset time.Last,the average for initial onset times of all selected components is calculated as the final onset time of this signal.This improved joint method is tested and validated by the acoustic signals with different signal to noise ratios(SNRs)and waveforms.The results show that the improved joint method is not affected by the variations of SNR,and the onset times picked by this method are always accurate in different SNRs.Moreover,the onset times of all acoustic signals with spikes,heavy bodies and unclear takeoffs can be accurately picked by the improved joint method.Compared to some other methods including MER,AIC,DWT-MER and DWT-AIC,the improved joint method has better SNR stabilities and waveform adaptabilities.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.
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.
基金National Key Research and Development Program of China(2022YFB2702800)National Natural Science Foundation of China(72334003)+1 种基金Shandong Key Research and Development Program(2020ZLYS09)Jinan Program(2021GXRC084-2)。
文摘Discrete wavelet transform(DWT)algorithm is an encryption algorithm based on wavelet transform for frequency decomposition of signals or images on multiple scales.Based on the Loongson 2K processor platform,the audio,picture and video information as carriers to encrypt and decrypt the watermark information is realized by integrating and stacking the watermark detection functions on the processor platform of the switching nodes in the off-chain communication network within blockchain systems,using the sliding window mechanism of Loongson 2K to control the smoothness of the digital information,and by multi-thread mechanism of the processor to control the real-time performance of the digital signal transmission.The performance of the least significant bit(LSB)algorithm,discrete cosine transform(DCT)algorithm,and DWT algorithm is analyzed.The performance comparison of LSB algorithm,DCT algorithm,and DWT algorithm under filtering attack,scaling attack,noise attack,cropping attack,and spin attack is simulated respectively.The experimental results show that,filtered attack normalized correlation(NC)coefficient for DWT is 0.95786,for scaled attack is 0.98962,for noise attack is 0.93842,spin attack NC is 0.86823,and clipped attack NC is 0.878814.The DWT algorithm has the small image distortion rate,is more robust to audio and video watermarking against attack effects,and the experimental data are superior to the LSB and DCT algorithms.Using Loongson 2K multi-threading mode to control the real-time data transmission,greatly improves the practicability of DWT algorithm on embedded devices,which can be effectively applied to authenticity verification when media data such as images and audio are uploaded to the blockchain.
基金Supported by National Science Fund for Distinguished Young Scholars(60625302)National Key Fundamental Research Project of China(2002CB3122000)National High Technology Research and Development Program of China(863 Program)(20060104Z1081)
文摘In this paper,shortcoming of traditional wavelet denoising in real-time signal processing is discussed,requirements of online denoising are considered,and a moving window is introduced into traditional wavelet transform.Using the moving window,an online wavelet denoising approach is proposed.Some problems of online denoising,such as border distortion and pseudo-Gibbs phenomena,are discussed.To solve these problems,window extension and window cycle spinning are also proposed.Different approaches are tested by the signal widely used in denoising domain.Both the visual results and the quantitative measures are presented to highlight the availability of the new approach.
基金Project(60772080) supported by the National Natural Science Foundation of ChinaProject(3240120) supported by Tianjin Subway Safety System, Honeywell Limited, China
文摘For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background model kept a sample of intensity values for each pixel in the image and used this sample to estimate the probability density function of the pixel intensity. The density function was estimated using a new Marr wavelet kernel density estimation technique. Since this approach was quite general, the model could approximate any distribution for the pixel intensity without any assumptions about the underlying distribution shape. The background and current frame were transformed in the binary discrete wavelet domain, and background subtraction was performed in each sub-band. After obtaining the foreground, shadow was eliminated by an edge detection method. Experimental results show that the proposed method produces good results with much lower computational complexity and effectively extracts the moving objects with accuracy ratio higher than 90%, indicating that the proposed method is an effective algorithm for intelligent transportation system.
基金Project(2015CB060200) supported by the National Basic Research Program of ChinaProject(41772313) supported by the National Natural Science Foundation of ChinaProject(2018zzts736) supported by the Independent Innovation Exploration Project of Central South University,China
文摘The onset times of acoustic signals with spikes,heavy bodies and unclear takeoffs are difficult to be picked accurately by the automatic method at present.To deal with this problem,an improved joint method based on the discrete wavelet transform(DWT),modified energy ratio(MER)and Akaike information criterion(AIC)pickers,has been proposed in this study.First,the DWT is used to decompose the signal into various components.Then,the joint application of MER and AIC pickers is carried out to pick the initial onset times of all selected components,where the minimum AIC position ahead of MER onset time is regarded as the initial onset time.Last,the average for initial onset times of all selected components is calculated as the final onset time of this signal.This improved joint method is tested and validated by the acoustic signals with different signal to noise ratios(SNRs)and waveforms.The results show that the improved joint method is not affected by the variations of SNR,and the onset times picked by this method are always accurate in different SNRs.Moreover,the onset times of all acoustic signals with spikes,heavy bodies and unclear takeoffs can be accurately picked by the improved joint method.Compared to some other methods including MER,AIC,DWT-MER and DWT-AIC,the improved joint method has better SNR stabilities and waveform adaptabilities.
