Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697264
A. Avanaki, A. Diyanat, S. Sodagari
Non-local means (a.k.a. NL-means) method for image de-noising averages the similar parts of an image to reduce random noise. The de-noising performance of the algorithm, however, highly depends on the values of its parameters. In this paper, we introduce a method for finding the optimum parameters, present a linear estimation for the h parameter, and demonstrate that the most important parameter in this method is almost independent of the image and depends only on the noise. We also show that the de-noising performance can be increased by using corner information of noisy image. Our modifications result in better de-noising performance at less computational cost.
{"title":"Optimum parameter estimation for non-local means image de-noising using corner information","authors":"A. Avanaki, A. Diyanat, S. Sodagari","doi":"10.1109/ICOSP.2008.4697264","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697264","url":null,"abstract":"Non-local means (a.k.a. NL-means) method for image de-noising averages the similar parts of an image to reduce random noise. The de-noising performance of the algorithm, however, highly depends on the values of its parameters. In this paper, we introduce a method for finding the optimum parameters, present a linear estimation for the h parameter, and demonstrate that the most important parameter in this method is almost independent of the image and depends only on the noise. We also show that the de-noising performance can be increased by using corner information of noisy image. Our modifications result in better de-noising performance at less computational cost.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127545392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697588
Yifeng Lu, Xiaolong Li, Wenfa Qi, Bin Yang
Recently, authentication of valuable documents has been widely studied and applied all over the world. One of the solutions for high-security authentication is optical watermark, which is different from traditional digital watermark in the way of watermark extraction. Optical watermark is detected by some optical and visual means. This paper discuss the optical watermark based on Moire phenomenon. We first elucidate the Moire phenomenon mathematically. Then we give an in-depth exploration of optical watermark based on phase modulation in a theoretical way. In addition, a security improvement with random noise is introduced to make the watermark harder to be cracked.
{"title":"A further study on an optical watermarking scheme","authors":"Yifeng Lu, Xiaolong Li, Wenfa Qi, Bin Yang","doi":"10.1109/ICOSP.2008.4697588","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697588","url":null,"abstract":"Recently, authentication of valuable documents has been widely studied and applied all over the world. One of the solutions for high-security authentication is optical watermark, which is different from traditional digital watermark in the way of watermark extraction. Optical watermark is detected by some optical and visual means. This paper discuss the optical watermark based on Moire phenomenon. We first elucidate the Moire phenomenon mathematically. Then we give an in-depth exploration of optical watermark based on phase modulation in a theoretical way. In addition, a security improvement with random noise is introduced to make the watermark harder to be cracked.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127022348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697340
Mingsong Dou, Chao Zhang, Daojing Wang
Rather than concentrating on modeling the image prior probability whose structure is defined locally, in this paper we incorporate the global information from a histogram into the Bayesian method for image de-noising. The key insight is that the histogram of an underlying image can be approximately recovered from the image with additive noise by a deconvolution operation. We test our algorithm in an image set commonly used for denoising test, and obtain improved results.
{"title":"Histogram-steered image denoising in the Bayesian framework","authors":"Mingsong Dou, Chao Zhang, Daojing Wang","doi":"10.1109/ICOSP.2008.4697340","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697340","url":null,"abstract":"Rather than concentrating on modeling the image prior probability whose structure is defined locally, in this paper we incorporate the global information from a histogram into the Bayesian method for image de-noising. The key insight is that the histogram of an underlying image can be approximately recovered from the image with additive noise by a deconvolution operation. We test our algorithm in an image set commonly used for denoising test, and obtain improved results.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127175297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697187
Ru-wei Li, C. Bao, Hui-jing Dou
Most of the current pitch detection algorithms can not work well under the high noise environment. For this reason, a pitch detection algorithm for noisy speech signal based on pre-filtering and weighted wavelet coefficients is proposed. Firstly, the noisy speech signals are pre-filtered. Secondly, the speech pre-filtered is decomposed by the quadratic spline wavelet. Thirdly, the wavelet coefficients of three consecutive scales are weighted to emphasize the sharp change points. Fourthly, three candidate pitch periods are extracted from the weighted signals. Finally, the pitch period is calculated by autocorrelation function. Experiments show that this algorithm can increase the performance of pitch detection in noisy environment and decreases computational complexity compared with DWT-NCCF method.
{"title":"Pitch detection method for noisy speech signals based on pre-filter and weighted wavelet coefficients","authors":"Ru-wei Li, C. Bao, Hui-jing Dou","doi":"10.1109/ICOSP.2008.4697187","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697187","url":null,"abstract":"Most of the current pitch detection algorithms can not work well under the high noise environment. For this reason, a pitch detection algorithm for noisy speech signal based on pre-filtering and weighted wavelet coefficients is proposed. Firstly, the noisy speech signals are pre-filtered. Secondly, the speech pre-filtered is decomposed by the quadratic spline wavelet. Thirdly, the wavelet coefficients of three consecutive scales are weighted to emphasize the sharp change points. Fourthly, three candidate pitch periods are extracted from the weighted signals. Finally, the pitch period is calculated by autocorrelation function. Experiments show that this algorithm can increase the performance of pitch detection in noisy environment and decreases computational complexity compared with DWT-NCCF method.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130058356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697627
Jingyao Liu, H. Meng, Xiqin Wang
Sea clutter refers to the radar returns from a patch of ocean surface. When a radar detects targets on or above the sea surface, it has to overcome the interference from sea echo itself. Sea clutter presents obviously non-Gaussian, non-stationary for many diverse factors, such as radar polarization mode, working frequency, antenna visual angle, sea state and wind direction, which limit the detection capability of radar. In this paper, we elaborate the production mechanism of sea clutter in detail and propose a new alpha-beta-gamma filter to suppress sea clutter and detect targets. In addition, the performance analysis and parameter choosing standard are given and the algorithm is proved to be effective with real data.
{"title":"Radar sea clutter suppression and target detection with α-β-γ filter","authors":"Jingyao Liu, H. Meng, Xiqin Wang","doi":"10.1109/ICOSP.2008.4697627","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697627","url":null,"abstract":"Sea clutter refers to the radar returns from a patch of ocean surface. When a radar detects targets on or above the sea surface, it has to overcome the interference from sea echo itself. Sea clutter presents obviously non-Gaussian, non-stationary for many diverse factors, such as radar polarization mode, working frequency, antenna visual angle, sea state and wind direction, which limit the detection capability of radar. In this paper, we elaborate the production mechanism of sea clutter in detail and propose a new alpha-beta-gamma filter to suppress sea clutter and detect targets. In addition, the performance analysis and parameter choosing standard are given and the algorithm is proved to be effective with real data.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123697979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697205
S. Seyedin, M. Ahadi
This paper proposes a new noise robust feature extraction method for speech recognition. It is based on the discrete cosine transform and minimum variance distortionless response (MVDR) methods of spectrum estimation and differential power spectrum technique. The large bias drawback of the periodogram method can be solved by using DCT instead of FFT. The MVDR method can also increase the robustness of the features by reducing the variance of the estimated power spectrum. The above method, when evaluated on Test set A of Aurora 2 task, gave a relative improvement of up to 63.3% in recognition accuracy in comparison with MFCC as the baseline.
{"title":"Feature extraction based on DCT and MVDR spectral estimation for robust speech recognition","authors":"S. Seyedin, M. Ahadi","doi":"10.1109/ICOSP.2008.4697205","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697205","url":null,"abstract":"This paper proposes a new noise robust feature extraction method for speech recognition. It is based on the discrete cosine transform and minimum variance distortionless response (MVDR) methods of spectrum estimation and differential power spectrum technique. The large bias drawback of the periodogram method can be solved by using DCT instead of FFT. The MVDR method can also increase the robustness of the features by reducing the variance of the estimated power spectrum. The above method, when evaluated on Test set A of Aurora 2 task, gave a relative improvement of up to 63.3% in recognition accuracy in comparison with MFCC as the baseline.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132450574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697386
Ying-kang Zhang, Yang Xiao
3D reconstruction is an important technique in the domain of computer vision. The existing systems of 3D reconstruction are often built on specialized hardware such as structured light or laser scanner with high cost. And some systems require intricate calibration procedures using complex calibration objects. These are not practical to reconstruct the 3D model of an arbitrary scene. In this paper, a flexible method of 3D reconstruction based on uncalibrated image sequence is proposed. This system consist a series of processes such as feature points extraction and match, projective reconstruction, self-calibration, dense match, and finally the dense surface of 3D model can be reconstructed. Experimental results prove that this method is practical and has higher precision.
{"title":"A practical method of 3D reconstruction based on uncalibrated image sequence","authors":"Ying-kang Zhang, Yang Xiao","doi":"10.1109/ICOSP.2008.4697386","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697386","url":null,"abstract":"3D reconstruction is an important technique in the domain of computer vision. The existing systems of 3D reconstruction are often built on specialized hardware such as structured light or laser scanner with high cost. And some systems require intricate calibration procedures using complex calibration objects. These are not practical to reconstruct the 3D model of an arbitrary scene. In this paper, a flexible method of 3D reconstruction based on uncalibrated image sequence is proposed. This system consist a series of processes such as feature points extraction and match, projective reconstruction, self-calibration, dense match, and finally the dense surface of 3D model can be reconstructed. Experimental results prove that this method is practical and has higher precision.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130900835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697712
Wei Chu, B. Champagne
In this paper, the noise-robustness of a recently proposed fast Fourier transform (FFT)-based auditory spectrum (FFT-AS) is further evaluated through speech/music/noise classification experiments wherein mismatched test cases are considered. The features obtained from the FFT-AS show more robust performance as compared to the conventional mel-frequency cepstral coefficient (MFCC) features. To further explore the FFT-AS from a perspective of practical audio classification, an audio classification algorithm using features derived from the FFT-AS is implemented on the floating-point DSP platform TMS320C6713. Through various optimization approaches, a significant reduction in the computational complexity is achieved wherein the implemented system demonstrates the ability to classify among speech, music and noise under the constraint of real-time processing.
{"title":"Further studies of a FFT-based auditory spectrum with application in audio classification","authors":"Wei Chu, B. Champagne","doi":"10.1109/ICOSP.2008.4697712","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697712","url":null,"abstract":"In this paper, the noise-robustness of a recently proposed fast Fourier transform (FFT)-based auditory spectrum (FFT-AS) is further evaluated through speech/music/noise classification experiments wherein mismatched test cases are considered. The features obtained from the FFT-AS show more robust performance as compared to the conventional mel-frequency cepstral coefficient (MFCC) features. To further explore the FFT-AS from a perspective of practical audio classification, an audio classification algorithm using features derived from the FFT-AS is implemented on the floating-point DSP platform TMS320C6713. Through various optimization approaches, a significant reduction in the computational complexity is achieved wherein the implemented system demonstrates the ability to classify among speech, music and noise under the constraint of real-time processing.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130249452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697601
Qu Chang-wen, Wang Ying, Chen Botao, S. Feng
There is a growing interest in the frequency modulated continuous wave (FMCW) SAR for its small cubage, light weight, cost-effective and high resolution. Imaging sensors based on pulsed radar technology are generally too heavy or too expensive. Frequency modulated continuous wave (FMCW) radars, however are usually more compact and less expensive. An FMCW synthetic aperture radar (SAR) combines the advantage of FMCW technology and SAR methods, leading to small, cost-effective imaging radar of high resolution. In this paper, the signal processing of the triangular wave, the removing of residual video phase (RVP)and the slope factor were deduced in detailed, then the data of the experiment was used to image. In the imaging, the up chirp of the return signal is used. The result proves the FMCW SAR can accomplish high resolution imaging.
{"title":"Using a FMCW SAR to image the corner-reflector","authors":"Qu Chang-wen, Wang Ying, Chen Botao, S. Feng","doi":"10.1109/ICOSP.2008.4697601","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697601","url":null,"abstract":"There is a growing interest in the frequency modulated continuous wave (FMCW) SAR for its small cubage, light weight, cost-effective and high resolution. Imaging sensors based on pulsed radar technology are generally too heavy or too expensive. Frequency modulated continuous wave (FMCW) radars, however are usually more compact and less expensive. An FMCW synthetic aperture radar (SAR) combines the advantage of FMCW technology and SAR methods, leading to small, cost-effective imaging radar of high resolution. In this paper, the signal processing of the triangular wave, the removing of residual video phase (RVP)and the slope factor were deduced in detailed, then the data of the experiment was used to image. In the imaging, the up chirp of the return signal is used. The result proves the FMCW SAR can accomplish high resolution imaging.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128760531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697433
Guan Lu-yang, Bao Ming, Zhang Peng, Li Xiao-dong
Peripheral auditory model is a promising method for target classification to extract feature from target acoustic signals. But the general cochlear filter bank is not appropriate for the vehicle acoustic signal because of the obvious difference between the vehicle signal and speech. In this paper, a new method to design the cochlear filter bank for vehicle classification was proposed on the principle of class separability of the patterns. On the basis of the modified peripheral auditory model, monaural model based cepstrum coefficient (MoMCC) was proposed as feature and applied to multi-class vehicle classification. Experimental results show that MoMCC improves both the classification rate and the robustness of the classifier, especially at low SNR.
{"title":"A Modified peripheral auditory model for vehicle classification","authors":"Guan Lu-yang, Bao Ming, Zhang Peng, Li Xiao-dong","doi":"10.1109/ICOSP.2008.4697433","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697433","url":null,"abstract":"Peripheral auditory model is a promising method for target classification to extract feature from target acoustic signals. But the general cochlear filter bank is not appropriate for the vehicle acoustic signal because of the obvious difference between the vehicle signal and speech. In this paper, a new method to design the cochlear filter bank for vehicle classification was proposed on the principle of class separability of the patterns. On the basis of the modified peripheral auditory model, monaural model based cepstrum coefficient (MoMCC) was proposed as feature and applied to multi-class vehicle classification. Experimental results show that MoMCC improves both the classification rate and the robustness of the classifier, especially at low SNR.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126845898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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