{"title":"Detection of coral distribution change in recent decades with satellite remote sensing","authors":"D. Yang, S. Liu, X. Shan","doi":"10.1109/CISP.2013.6745280","DOIUrl":"https://doi.org/10.1109/CISP.2013.6745280","url":null,"abstract":"Coral reef is a very important ecosystem in Sanya Bay and it has been studied for years only with in situ observations. However, these in situ observations generally have point information and lack the spatial resolution. Recently in order to make clear coral reef spatial distribution and variation in Sanya Bay, Hainan, satellite data of Landsat, QuickBird, CBERS (China-Brazil Earth Resources Satellite program) and historical in situ observation data are used to retrieve and validate the information of coral reef. Based on the retrieved information, coral reef coverage and variation were studied in the paper. Satellite remote sensing results showed that area of coral reef distribution along coast of Dongmao (east) Islands and Ximao (west) islands in Sanya Bay reduced greatly in recent years, which coincides with variation trends of in situ observation data in the whole Sanya Bay. While analyzing the reason for coral reduction it was found that coral distribution in Sanya Bay conversely correlated with anthropic activities, such as digging coral reef for making lime and land use change. These activities change the water quality and sediment type which lead to the change in coral distribution.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128061569","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}
Jun Luo, Qijun Huang, Sheng Chang, Xiaoying Song, Yun Shang
{"title":"High throughput Cholesky decomposition based on FPGA","authors":"Jun Luo, Qijun Huang, Sheng Chang, Xiaoying Song, Yun Shang","doi":"10.1109/CISP.2013.6743941","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743941","url":null,"abstract":"Cholesky decomposition has wide applications in solving many engineering and scientific problems. Acceleration is an important issue in many of these problems. In this paper, a hardware-based LLT Cholesky decomposition featuring high throughput has been presented to solve wiener filtering based on the minimum square error criterion. To achieve the best efficiency, the hardware-based implementation has been realized by fixed-point multiple structures and various pipeline stages. Parallel properties have been exploited to improve the throughput. Results have shown that a significant speedup has been achieved compared to the software-based approach.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125616090","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}
Yi-Long Wan, Tian-qi Zhang, Zhi-Chao Wang, Jing Jin
{"title":"Robust speech recognition based on multi-band spectral subtraction","authors":"Yi-Long Wan, Tian-qi Zhang, Zhi-Chao Wang, Jing Jin","doi":"10.1109/CISP.2013.6744019","DOIUrl":"https://doi.org/10.1109/CISP.2013.6744019","url":null,"abstract":"In order to reduce the degradation of the speech recognition accuracy while the testing condition are mismatched with the training condition around noisy environment, a kind of multi-band spectral subtraction has been proposed. The estimated noise signals were extracted from the first few frames of the noisy speech. The noisy speech and estimation of noise signals by the frequency were divided into non-overlapping M frequency bands. According to the SNR (signal-to-noise ratio) of noise speech in each frequency band, the band noise spectral subtraction parameters can be determined. The front-end speech enhancement module and the speech recognizer constitute a robust speech recognition system. The results of simulation experiments indicate that the recognition accuracy of multi-band spectral subtraction robust speech recognition system is obviously superior to the basic spectral subtraction in different signal-to-noise ratios and different noise's types.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132392164","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}
{"title":"Electricity price forecasting by clustering-least squares support vector machine","authors":"Li Xie, Hua Zheng","doi":"10.1109/CISP.2013.6743884","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743884","url":null,"abstract":"In the electricity market, the price as the lever results in the dramatic variations, especially, the capacity or willingness of electricity consumers and then demand may be low, particularly over short time frames. Therefore demand-side management (DSM) has been put into practice, and the market supervisors become more and more focused on the price dynamics of the short-term, because of its effects on the modification of consumer demand for energy through various methods especially financial incentives. But due to the complexity of the price, the electricity price forecasting is along one of focused and unsolved problems in the researches of electricity market. This paper describes a novel model for price forecasting is proposed by the developed least squares support vector machine (LS-SVM), which integrates Clustering algorithm with LS-SVM. First, clustering of the data samples are performed, which aims at mining the latent patterns in the data. After that, LS-SVM is applied for the nonlinear regression modeling of electricity price and its influence factors signed with its class, which results in a more efficient training and forecasting. Finally, hourly prices and loads of different market are employed to test the proposed approach.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134194539","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}
{"title":"Waterline information extraction from radial sand ridge of south yellow sea","authors":"P. Qin","doi":"10.1109/CISP.2013.6744038","DOIUrl":"https://doi.org/10.1109/CISP.2013.6744038","url":null,"abstract":"The radial sand ridge of south yellow sea is the biggest in the world. It has unique combination of factors in dynamic geomorphology. In order to study the trend prediction of beach evolution in radial sand ridge, waterline, which is the best expression for the complex terrain of the seashore intertidal region, is indispensible for research in the region. The study gain the best method to extract the waterline exactly and clearly, by experiment for the combinations of some kinds of edge extracting algorithm and image binaryzation algorithm. The result of this study provides an effective processing method for tidal beach shape and landscape description.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131683365","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}
{"title":"A novel prewhitening subspace method for enhancing speech corrupted by colored noise","authors":"Q. Wei, Youshen Xia, Shubiao Jiang","doi":"10.1109/CISP.2013.6743870","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743870","url":null,"abstract":"In this paper, we propose an improved subspace method for speech enhancement in the presence of colored noise, based on a novel prewhitening technique. The colored noise modeled as autoregressive (AR) process is first used for the AR parameter estimation. Then the speech model in colored noise is changed into the one in white noise, by multiplying the noisy speech by the whitening matrix constructed by the AR parameters. Because of the novel prewhitening technique, the proposed subspace method for speech enhancement can efficiently deal with colored noise. Compared with existing subspace method, the proposed subspace method overcomes difficulty in estimating covariance matrix of colored noise. Simulation shows that the proposed approach has better performance than three conventional algorithms.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131695722","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}
{"title":"Human motion capture data segmentation based on graph partition","authors":"Na Lv, Zhiquan Feng, Xiuyang Zhao","doi":"10.1109/CISP.2013.6745223","DOIUrl":"https://doi.org/10.1109/CISP.2013.6745223","url":null,"abstract":"For better reuse of motion capture data, long motion sequences need to be segmented into multiple motion clips of simple motion types. In this paper, we propose a method for motion capture data segmentation based on graph partition. Each frame of motion sequence is viewed as a node in an undirected weighted graph, and the weight of an edge is the similarity between two frames corresponding to the two nodes connected by the edge. The optimal segmentation is obtained through graph partition algorithm, which makes the similarities of nodes in each subgraph being high, and the similarities between different subgraphs being low. After the segment scores at each frame are calculated, double thresholds decision method is conducted on the score curve to detect segment points. Experimental results show that our method obtains good segmentation results.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130754946","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}
{"title":"Probabilistic latent component analysis for radar signal detection","authors":"Tao Ying, Gaoming Huang, Cheng Zhou","doi":"10.1109/CISP.2013.6743931","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743931","url":null,"abstract":"The detection of radar signal submerged in noise has always been substantial for radar performance. An algorithm of radar signal detection based on probabilistic latent component analysis is proposed in this paper. By employing probabilistic latent component analysis, signal spectrogram is explicitly modeled as a mixture of marginal distribution products and noise is described by a dictionary of marginals. The estimation of the most appropriate marginal distributions is performed using Expectation-Maximization algorithm. The goal of signal detection is achieved by selective reconstruction method of extracting signal from noise. Simulation results demonstrate the effectiveness of the proposed algorithm and the improvement of signal detection over wavelet detection.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132924391","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}
{"title":"Plane-curve-based matching for broken bronze mirror reassembling","authors":"Wuyang Shui, Mingquan Zhou, Liyang Zhang, Y. Wang","doi":"10.1109/CISP.2013.6745308","DOIUrl":"https://doi.org/10.1109/CISP.2013.6745308","url":null,"abstract":"Bronze mirror is one of the most famous bronze artifacts in ancient China, some of which have been broken into several small fractures after excavation. Recently, computer scientists collaborating with archeologists focused on fractures matching automatically according to geometry curve. In this paper, a novel method is proposed for several fractures automatic reassembling to improve the speed and accuracy. Firstly, the one-shot image is utilized to collect image data for broken bronze mirror by digital camera. Secondly, watershed algorithm is used to segment and mark each fracture. Thirdly, the longest common curve is found by combining corners detection, coarse matching and fine matching, taking length, angle and curvature into account. The curvature consistency is used to omit the outlier mirror external curve to guarantee matching correctly by circle-shaped structure. Finally, the least square method is performed to compute rigid transformation to reassemble neighbor fractures by matching increment. Experimental results on broken bronze mirror demonstrate the correctness and robustness of our method.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132256801","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}
{"title":"Image denoising using spatial domain filters: A quantitative study","authors":"Anmol Sharma, Jagroop Singh","doi":"10.1109/CISP.2013.6744005","DOIUrl":"https://doi.org/10.1109/CISP.2013.6744005","url":null,"abstract":"Image denoising is the first preprocessing step dealing with image processing. In image denoising an image is processed using certain restoration techniques to remove induced noise which may creep in the image during acquisition, transmission or compression process. Examples of noise in an image can be Additive White Gaussian Noise (AWGN), Impulse Noise, etc. The goal of restoration techniques is to obtain an image that is as close to the original input image as possible. In this paper objective evaluation methods are used to judge the efficiency of different types of spatial domain filters applied to different noise models, with a quantitative approach. Performance of each filter is compared as they are applied on images affected by a wide variety of noise models. Conclusions are drawn in the end, about which filter is best suited for a number of noise models individually induced in an image, according to the experimental data obtained.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132428584","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}