In this letter, a new Linde-Buzo-Gray (LBG)-based image compression method using Discrete Cosine Transform (DCT) and Vector Quantization (VQ) is proposed. A gray-level image is firstly decomposed into blocks, then eac...In this letter, a new Linde-Buzo-Gray (LBG)-based image compression method using Discrete Cosine Transform (DCT) and Vector Quantization (VQ) is proposed. A gray-level image is firstly decomposed into blocks, then each block is subsequently encoded by a 2D DCT coding scheme. The dimension of vectors as the input of a generalized VQ scheme is reduced. The time of encoding by a generalized VQ is reduced with the introduction of DCT process. The experimental results demonstrate the efficiency of the proposed method.展开更多
To enhance the ability of remote sensing system to provide accurate,timely,and complete geo_spatial information at regional or global scale,an automated change detection system has been and will continue to be one of ...To enhance the ability of remote sensing system to provide accurate,timely,and complete geo_spatial information at regional or global scale,an automated change detection system has been and will continue to be one of the important and challenging problems in remote sensing.In this paper,the authors propose a framework for automated change detection system at landscape level using various geo_spatial data sources including multi_sensor remotely sensed imagery and ancillary data layers.In this framework,database is the central part and some associated techniques are discussed.These techniques includes five subsystems:automated feature_based image registration,automated change finding,automated change feature extraction and identification,intelligent change recognition,change accuracy assessment and database updating and visualization.展开更多
This paper introduces an image processing technique into seismic data processing as a noise attenuation technology. The image separation of the seismic profile is obtained by using grating operators based on different...This paper introduces an image processing technique into seismic data processing as a noise attenuation technology. The image separation of the seismic profile is obtained by using grating operators based on different time dips and a set of relative single dip profiles is obtained. A high signal to noise ratio profile can be obtained during reconstruction by statistical weighting. With further processing analysis and geological study, a high signal to noise profile that can meet geological requirements can be produced. The real data examples show that the signal to noise ratio of the profile is greatly improved, the resolution of the profile is maintained, and the fault terminations are much clearer after using the image processing method.展开更多
Monitoring algal blooms by optical remote sensing is limited by cloud cover.In this study,synthetic aperture radar(SAR) was deployed with the aim of monitoring cyanobacteria-dominant algal blooms in Taihu Lake in clou...Monitoring algal blooms by optical remote sensing is limited by cloud cover.In this study,synthetic aperture radar(SAR) was deployed with the aim of monitoring cyanobacteria-dominant algal blooms in Taihu Lake in cloudy weather.The study shows that dark regions in the SAR images caused by cyanobacterial blooms damped the microwave backscatter of the lake surface and were consistent with the regions of algal blooms in quasi-synchronous optical images,confirming the applicability of SAR for detection of surface blooms.Low backscatter may also be associated with other factors such as low wind speeds,resulting in interference when monitoring algal blooms using SAR data alone.After feature extraction and selection,the dark regions were classified by the support vector machine method with an overall accuracy of 67.74%.SAR can provide a reference point for monitoring cyanobacterial blooms in the lake,particularly when weather is not suitable for optical remote sensing.Multi-polarization and multi-band SAR can be considered for use in the future to obtain more accurate information regarding algal blooms from SAR data.展开更多
In this paper, we propose an improved Directed Acyclic Graph Support Vector Machine （DAGSVM） for multi-class classification. Compared with the traditional DAGSVM, the improved version has advantages that the structu...In this paper, we propose an improved Directed Acyclic Graph Support Vector Machine （DAGSVM） for multi-class classification. Compared with the traditional DAGSVM, the improved version has advantages that the structure of the directed acyclic graph is not chosen random and fixed, and it can be adaptive to be optimal according to the incoming testing samples, thus it has a good generalization performance. From experiments on six datasets, we can see that the proposed improved version of DAGSVM is better than the traditional one with respect to the accuracy rate.展开更多
基金Partially supported by the National Natural Science Foundation of China (No.60572100), Foundation of State Key Laboratory of Networking and Switching Technology (China) and Science Foundation of Shenzhen City (200408).
文摘In this letter, a new Linde-Buzo-Gray (LBG)-based image compression method using Discrete Cosine Transform (DCT) and Vector Quantization (VQ) is proposed. A gray-level image is firstly decomposed into blocks, then each block is subsequently encoded by a 2D DCT coding scheme. The dimension of vectors as the input of a generalized VQ scheme is reduced. The time of encoding by a generalized VQ is reduced with the introduction of DCT process. The experimental results demonstrate the efficiency of the proposed method.
文摘To enhance the ability of remote sensing system to provide accurate,timely,and complete geo_spatial information at regional or global scale,an automated change detection system has been and will continue to be one of the important and challenging problems in remote sensing.In this paper,the authors propose a framework for automated change detection system at landscape level using various geo_spatial data sources including multi_sensor remotely sensed imagery and ancillary data layers.In this framework,database is the central part and some associated techniques are discussed.These techniques includes five subsystems:automated feature_based image registration,automated change finding,automated change feature extraction and identification,intelligent change recognition,change accuracy assessment and database updating and visualization.
基金This research is sponsored by China National Natural Science Foundation （No. 40574050, No. 40521002） and CNPC Innovation Fund （04E702）.
文摘This paper introduces an image processing technique into seismic data processing as a noise attenuation technology. The image separation of the seismic profile is obtained by using grating operators based on different time dips and a set of relative single dip profiles is obtained. A high signal to noise ratio profile can be obtained during reconstruction by statistical weighting. With further processing analysis and geological study, a high signal to noise profile that can meet geological requirements can be produced. The real data examples show that the signal to noise ratio of the profile is greatly improved, the resolution of the profile is maintained, and the fault terminations are much clearer after using the image processing method.
基金Supported by the High Resolution Earth Observation Systems of National Science and Technology Major Projects(No.05-Y30B02-9001-13/155)the National High Technology Research and Development Program of China(Nos.2012AA12A301,2013AA12A302)the Key Basic Research Project of the Science and Technology Commission of Shanghai Municipality(No.12510502000)
文摘Monitoring algal blooms by optical remote sensing is limited by cloud cover.In this study,synthetic aperture radar(SAR) was deployed with the aim of monitoring cyanobacteria-dominant algal blooms in Taihu Lake in cloudy weather.The study shows that dark regions in the SAR images caused by cyanobacterial blooms damped the microwave backscatter of the lake surface and were consistent with the regions of algal blooms in quasi-synchronous optical images,confirming the applicability of SAR for detection of surface blooms.Low backscatter may also be associated with other factors such as low wind speeds,resulting in interference when monitoring algal blooms using SAR data alone.After feature extraction and selection,the dark regions were classified by the support vector machine method with an overall accuracy of 67.74%.SAR can provide a reference point for monitoring cyanobacterial blooms in the lake,particularly when weather is not suitable for optical remote sensing.Multi-polarization and multi-band SAR can be considered for use in the future to obtain more accurate information regarding algal blooms from SAR data.
文摘In this paper, we propose an improved Directed Acyclic Graph Support Vector Machine （DAGSVM） for multi-class classification. Compared with the traditional DAGSVM, the improved version has advantages that the structure of the directed acyclic graph is not chosen random and fixed, and it can be adaptive to be optimal according to the incoming testing samples, thus it has a good generalization performance. From experiments on six datasets, we can see that the proposed improved version of DAGSVM is better than the traditional one with respect to the accuracy rate.
