Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770282
Sun Xun, Limin Du, Wei-Yean Howng
It is very difficult but very important to get higher quantity at lower bit rate in the field of speech coding. Traditional vocoders, such as LPC10e and CELPC, can give acceptable results but suffer from a hoarse output. We attribute this problem to the inconsistency between the equal resolution characteristic of linear prediction throughout the whole frequency band and the characteristic of the human ear's unequal resolution at different frequency bands. In this paper, we present a new wavelet linear prediction subband coding algorithm (WLPSC), by employing a wavelet filter bank based on the auditory model. We divide the input speech signal into four subbands, and then code each subband respectively. Experimental results show that this algorithm can greatly reduce the hoarse output of vocoders.
{"title":"Wavelet linear prediction vocoder based on auditory model","authors":"Sun Xun, Limin Du, Wei-Yean Howng","doi":"10.1109/ICOSP.1998.770282","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770282","url":null,"abstract":"It is very difficult but very important to get higher quantity at lower bit rate in the field of speech coding. Traditional vocoders, such as LPC10e and CELPC, can give acceptable results but suffer from a hoarse output. We attribute this problem to the inconsistency between the equal resolution characteristic of linear prediction throughout the whole frequency band and the characteristic of the human ear's unequal resolution at different frequency bands. In this paper, we present a new wavelet linear prediction subband coding algorithm (WLPSC), by employing a wavelet filter bank based on the auditory model. We divide the input speech signal into four subbands, and then code each subband respectively. Experimental results show that this algorithm can greatly reduce the hoarse output of vocoders.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114055945","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770335
P. Skocir, B. Marusic, J. Tasic
We present the results of a preliminary study of enhancement of images that have been degraded by lossy wavelet coding algorithms. In this preliminary study we tested a large set of (nonlinear) image enhancement algorithms. The results have been evaluated using a simple objective criterion, which has been found to have reasonable correlation to subjective quality estimation for wavelet-degraded images. We first discuss some of the aspects of lossy wavelet coding and the associated degradation. Then we briefly outline the proposed quality measure. Finally we present the postprocessing algorithm which was found to be optimal for image enhancement after the abovementioned kind of degradation.
{"title":"Evaluation of postprocessing stages for wavelet-compressed image enhancement based on a simple perceptual criteria","authors":"P. Skocir, B. Marusic, J. Tasic","doi":"10.1109/ICOSP.1998.770335","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770335","url":null,"abstract":"We present the results of a preliminary study of enhancement of images that have been degraded by lossy wavelet coding algorithms. In this preliminary study we tested a large set of (nonlinear) image enhancement algorithms. The results have been evaluated using a simple objective criterion, which has been found to have reasonable correlation to subjective quality estimation for wavelet-degraded images. We first discuss some of the aspects of lossy wavelet coding and the associated degradation. Then we briefly outline the proposed quality measure. Finally we present the postprocessing algorithm which was found to be optimal for image enhancement after the abovementioned kind of degradation.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115595828","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770829
Z. Chi, Jun Kong
Image content classification is a very important step in document image analysis and understanding, and page-segmentation-based document image compression. In this paper, we present an new approach to classifying image content using block Kolmogorov complexity (KC) measures. A binarized two-dimensional image is first partitioned into blocks and each block image is converted into a one-dimensional binary sequence using either horizontal or vertical scanning. The block complexities are then computed over the obtained binary sequences. An image is classified into one of two categories, textual or pictorial images, using two fuzzy rules with the mean value and the standard deviation of block complexities. Experimental results on eight Chinese/English textual images of different fonts and eight different pictorial images show that our approach is reliable in discriminating these two types of images. Moreover, the performance of our method, where a training process is not required, is comparable to that of a neural network technique.
{"title":"Image content classification using a block Kolmogorov complexity measure","authors":"Z. Chi, Jun Kong","doi":"10.1109/ICOSP.1998.770829","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770829","url":null,"abstract":"Image content classification is a very important step in document image analysis and understanding, and page-segmentation-based document image compression. In this paper, we present an new approach to classifying image content using block Kolmogorov complexity (KC) measures. A binarized two-dimensional image is first partitioned into blocks and each block image is converted into a one-dimensional binary sequence using either horizontal or vertical scanning. The block complexities are then computed over the obtained binary sequences. An image is classified into one of two categories, textual or pictorial images, using two fuzzy rules with the mean value and the standard deviation of block complexities. Experimental results on eight Chinese/English textual images of different fonts and eight different pictorial images show that our approach is reliable in discriminating these two types of images. Moreover, the performance of our method, where a training process is not required, is comparable to that of a neural network technique.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115616110","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770222
L. Hoteit
The Moulines subspace procedure (Moulines et al., 1995), for blind identification leads to an inconsistent estimation when the order of the channel is unknown or when it is close to being unidentifiable. The non-robustness of the subspace approach to order over-estimation is considered a major limitation to its use in practical situations. This is usually the strongest argument in favour of linear prediction-based methods for channel identification. In this contribution, we propose a simple extension to the subspace approach which is robust to both over-estimation and lack of channel disparity.
Moulines子空间过程(Moulines et al.， 1995)用于盲识别，当信道的阶数未知或接近不可识别时，会导致估计不一致。序过估计子空间方法的非鲁棒性被认为是限制其在实际应用中的一个主要问题。这通常是支持基于线性预测的通道识别方法的最有力的论据。在这篇文章中，我们提出了一种简单的子空间方法的扩展，该方法对信道过估计和信道视差缺乏都具有鲁棒性。
{"title":"Extending the subspace method for blind identification","authors":"L. Hoteit","doi":"10.1109/ICOSP.1998.770222","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770222","url":null,"abstract":"The Moulines subspace procedure (Moulines et al., 1995), for blind identification leads to an inconsistent estimation when the order of the channel is unknown or when it is close to being unidentifiable. The non-robustness of the subspace approach to order over-estimation is considered a major limitation to its use in practical situations. This is usually the strongest argument in favour of linear prediction-based methods for channel identification. In this contribution, we propose a simple extension to the subspace approach which is robust to both over-estimation and lack of channel disparity.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114254589","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770940
Jie Ding, Y. Aoki
An interactive system is developed for efficient processing of remote sensing meteorological data, which focuses on scientific visualization of radar reflectivity intensity data and compression of satellite cloud picture. Using this interactive system, reflectivity intensity numerical data with vast size observed by radar can be visualized in color maps almost at real-time, and satellite cloud pictures can be compressed by fractal image compression, which can help us to draw meaningful weather information out of the numerical data conveniently, and transmit a satellite cloud picture quickly.
{"title":"An interactive system for remote sensing meteorological data processing","authors":"Jie Ding, Y. Aoki","doi":"10.1109/ICOSP.1998.770940","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770940","url":null,"abstract":"An interactive system is developed for efficient processing of remote sensing meteorological data, which focuses on scientific visualization of radar reflectivity intensity data and compression of satellite cloud picture. Using this interactive system, reflectivity intensity numerical data with vast size observed by radar can be visualized in color maps almost at real-time, and satellite cloud pictures can be compressed by fractal image compression, which can help us to draw meaningful weather information out of the numerical data conveniently, and transmit a satellite cloud picture quickly.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114487756","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770871
Zhang Qing, Wang Shu
The ART-2 neural network is a self-organized artificial network that operates according to adaptive resonance theory. A neuro-fuzzy network, which combines ART-2 and the fuzzy system in series, is presented and applied to fire detection. The results of experiments show that this system has a stronger ability to adapt to the environment than the backpropagation (BP) neural network. It can detect various standard test fires more rapidly and accurately, and has strong anti-interference capability.
{"title":"A fire detection system based on ART-2 neuro-fuzzy network","authors":"Zhang Qing, Wang Shu","doi":"10.1109/ICOSP.1998.770871","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770871","url":null,"abstract":"The ART-2 neural network is a self-organized artificial network that operates according to adaptive resonance theory. A neuro-fuzzy network, which combines ART-2 and the fuzzy system in series, is presented and applied to fire detection. The results of experiments show that this system has a stronger ability to adapt to the environment than the backpropagation (BP) neural network. It can detect various standard test fires more rapidly and accurately, and has strong anti-interference capability.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116159744","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770246
Peng Hua, Le Zhongxin
A blind equalization algorithm based on the unsupervised Gaussian cluster formation technique with a robust adaptive step-size to update the equalizer coefficients is proposed. In order to guarantee the convergence of the algorithm, the algorithm runs in a "stop-and-go" operation mode in such a way that a Godard class of algorithm controls its "stop-and-go" operation. In order to achieve faster convergence speed, the algorithm is switched to a Godard class of algorithm when adaptation is stopped. Simulation results confirm the effectiveness of the proposed algorithm on high-order QAM signals.
{"title":"A new blind equalizer for high-order QAM system","authors":"Peng Hua, Le Zhongxin","doi":"10.1109/ICOSP.1998.770246","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770246","url":null,"abstract":"A blind equalization algorithm based on the unsupervised Gaussian cluster formation technique with a robust adaptive step-size to update the equalizer coefficients is proposed. In order to guarantee the convergence of the algorithm, the algorithm runs in a \"stop-and-go\" operation mode in such a way that a Godard class of algorithm controls its \"stop-and-go\" operation. In order to achieve faster convergence speed, the algorithm is switched to a Godard class of algorithm when adaptation is stopped. Simulation results confirm the effectiveness of the proposed algorithm on high-order QAM signals.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116279217","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770275
H.R.S. Mohammadi
Sorted codebook vector quantization (SCVQ) is shown to be a very efficient vector quantization method. Generalization of SCVQ is suggested and its application to the spectral coding of speech using the quantization of line spectral frequencies (LSF), which are the most popular parameters to represent the linear prediction model for spectrum quantization in speech coders, is described. Computer simulations are conducted to evaluate the performance of the new method. We demonstrate that the new method achieves superior quality and has low implementation costs.
{"title":"Spectral coding of speech based on generalized sorted codebook vector quantization","authors":"H.R.S. Mohammadi","doi":"10.1109/ICOSP.1998.770275","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770275","url":null,"abstract":"Sorted codebook vector quantization (SCVQ) is shown to be a very efficient vector quantization method. Generalization of SCVQ is suggested and its application to the spectral coding of speech using the quantization of line spectral frequencies (LSF), which are the most popular parameters to represent the linear prediction model for spectrum quantization in speech coders, is described. Computer simulations are conducted to evaluate the performance of the new method. We demonstrate that the new method achieves superior quality and has low implementation costs.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115260751","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770145
Wang Chengyi, Wang Hongyu
Conventional estimation methods for the cyclic spectra of cyclostationary processes are the temporally smoothed cyclic periodogram and the spectrally smoothed cyclic periodogram. In the case of short data records, both methods have low resolution and bad reliability. This paper uses maximum likelihood filters with modified analysis effective bandwidth to estimate cyclic spectra. Good performance in terms of resolution and reliability can be obtained using this method.
{"title":"Estimation of cyclic spectra using maximum likelihood filters","authors":"Wang Chengyi, Wang Hongyu","doi":"10.1109/ICOSP.1998.770145","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770145","url":null,"abstract":"Conventional estimation methods for the cyclic spectra of cyclostationary processes are the temporally smoothed cyclic periodogram and the spectrally smoothed cyclic periodogram. In the case of short data records, both methods have low resolution and bad reliability. This paper uses maximum likelihood filters with modified analysis effective bandwidth to estimate cyclic spectra. Good performance in terms of resolution and reliability can be obtained using this method.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123711309","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 : 1998-10-12DOI: 10.1109/ICOSP.1998.770260
S. Nishimura, Hai-Yun Jiang, T. Hinamoto
We present a new structure for complex adaptive IIR notch filters which is useful for the rejection of narrowband interference from broadband signals in QPSK communications systems. The proposed structure is based on a gradient algorithm. A performance analysis for convergence properties is developed. It is shown that the convergence speed does not depend on the variance of input white noise. The effects of colored Gaussian noise on convergence speed are analyzed. The results of computer simulation are shown which confirm the theoretical prediction.
{"title":"Performance analysis of complex adaptive IIR notch filters","authors":"S. Nishimura, Hai-Yun Jiang, T. Hinamoto","doi":"10.1109/ICOSP.1998.770260","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770260","url":null,"abstract":"We present a new structure for complex adaptive IIR notch filters which is useful for the rejection of narrowband interference from broadband signals in QPSK communications systems. The proposed structure is based on a gradient algorithm. A performance analysis for convergence properties is developed. It is shown that the convergence speed does not depend on the variance of input white noise. The effects of colored Gaussian noise on convergence speed are analyzed. The results of computer simulation are shown which confirm the theoretical prediction.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124500245","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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