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PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform

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Acta Oceanologica Sinica 2015年第3期34卷 59-67页

作者： LIU Meijie DAI Yongshou ZHANG Jie ZHANG Xi MENG Junmin XIE Qinchuan China University of Petroleum (Huadong) First Institute of Oceanography State Oceanic Administration Qingdao University

Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral in-formation, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be im-proved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transfor-mation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar （ASAR） loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensi-ty-saturation （HIS） space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue （RGB） space, and the optical image from the China-Brazil Earth Resources Satellite （CBERS-02B） was transferred from the RGB space to the HIS space. The principal component analysis （PCA） method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice ident

关键词： sea ice optical remote sensing image SAR remote sensing image HIS transform wavelet transform PCA method

APPLICATION OF wavelet transform TO BIFURCATION AND CHAOS STUDY

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Applied Mathematics and Mechanics(English Edition) 1998年第6期19卷 593-599页

作者：郑吉兵高行山郭银朝 Department of Applied Mechanics and Engineering Southwest Jiaotong University Chengdu 610031 China Institute of Vibration Engineering Northwestern Polytechnical University Xi'an 710072 China

The response of a nonlinear vibration system may be of three types, namely, periodic, quasiperiodic or chaotic,,when the parameters of the system are changed. The periodic motions can be identified by Poincare map, and harmonic wavelet transform (HWT) can distinguish quasiperiod from chaos, so the existing domains of different types of motions of the system can be revealed in the parametric space with the method of HWT joining with Poincare map.

关键词： wavelet transform nonlinear vibration bifurcation chaos

EXTENDED SELF SIMILARITY OF PASSIVE SCALAR IN RAYLEIGH-BNARD CONVECTION FLOW BASED ON wavelet transform

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Applied Mathematics and Mechanics(English Edition) 2002年第7期23卷 804-810页

作者：傅强夏克青 College of Physics Meterology Institute of Science and Engineering University of PLA Nanjing P R China Department of Physics Chinese University of Hong Kong Shatian Hong KongP R China

Wavetet transform was used to analyze the scaling law of temperature data (passive scalar) in Rayleigh-Bénard convection flow from two aspects. The first one was to utilize the method of extended self similarity, presented first by Benzi et al., to study the scaling exponent of temperature data. The obtained results show that the inertial range is much wider than that one determined directly from the conventional structure function, and find the obtained scaling exponent agrees well with the one obtained from the temperature data in an experiment of wind tunnel. The second one was that, by extending the formula which was proposed by A. Arneodo et al. for extracting the scaling exponent ζ(q) of velocity data to temperature data, a newly defined formula which is also based on wavelet transform, and can determine the scaling exponent ξ(q) of temperature data was proposed. The obtained results demonstrate that by using the method which is named as WTMM (wavelet transform maximum modulus) ξ(q) correctly can be extracted.

关键词： Rayleigh-Bénard convection wavelet transform extended self similarity scaling law temperature data

New algorithm for infrared small target image enhancement based on wavelet transform and human visual properties

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Journal of Systems Engineering and Electronics 2006年第2期17卷 268-273页

作者： Wang Xuewei Liu Songtao Zhou Xiaodong Automatic Control Engineering Dept. Naval Aeronautical Engineering Inst. Yantai 264001 P. R. China

The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm（WDIDA）, which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performanee , preserving edges and improving the visual quality of images.

关键词： image enhancement wavelet transform human visual properties inclusive-OR.

A novel out of step relaying algorithm based on wavelet transform and a deep learning machine model

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Protection and Control of Modern Power Systems 2021年第1期6卷 500-511页

作者： Jigneshkumar Pramodbhai Desai Vijay Hiralal Makwana Gujarat Technological University ChandkhedaAhmedabad382424GujaratIndia Electrical Engineering Department U.V.Patel College of EngineeringGanpat UniversityKhervaMehsana384012GujaratIndia Electrical Engineering Department G.H.Patel College of Engineering and TechnologyCVM UniversityBakrol RoadAnand388120GujaratIndia

Out-of-step protection of one or a group of synchronous generators is unreliable in a power system which has significant renewable power penetration. In this work, an innovative out-of-step protection algorithm using wavelet transform and deep learning is presented to protect synchronous generators and transmission lines. The specific patterns are generated from both stable and unstable power swing, and three-phase fault using the wavelet transform technique. Data containing 27,008 continuous samples of 48 different features is used to train a two-layer feed-forward network. The proposed algorithm gives an automatic, setting free and highly accurate classification for the three-phase fault, stable power swing, and unstable power swing through pattern recognition within a half cycle. The proposed algorithm uses the Kundur 2-area system and a 29-bus electric network for testing under different swing center locations and levels of renewable power penetration. Hardware-in-the-loop (HIL) tests show the hardware compatibility of the developed out-of-step algorithm. The proposed algorithm is also compared with recently reported algorithms. The comparison and test results on different large-scale systems show that the proposed algorithm is simple, fast, accurate, and HIL tested, and not affected by changes in power system parameters.

关键词： Classification Deep learning Out of Step Detection Power swing wavelet transform

Identification of diesel front sound source based on continuous wavelet transform

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Journal of Zhejiang University Science 2004年第9期5卷 1069-1075页

作者：郝志勇韩军 CollegeofMechanicalandEnergyEngineering ZhejiangUniversityHangzhou310027China SchoolofMechanicalEngineering TianjinUniversityTianjin300072China

Acoustic signals from diesel engines contain useful information but also include considerable noise components To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals. wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level. Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.

关键词： Acoustic signals wavelet transform Diesel engine Sound source identification

Contour Matching Using wavelet transform and Multigrid Methods

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Journal of Computer Science & Technology 1997年第6期12卷 564-570页

作者：蒋田仔马颂德 SchoolofMathematics TheUniversityofNewSouthWalesSydney2052Australia NationalLaboratoryofPatternRecog

In this paper, wavelet transform and multigrid method are combined to make the method more practical. It is known that Gaussian filtering causes shrinkage of data. To overcome this disadvantage, Gaussian filtering is replaced with wavelet transform. This method introduces no curve shrinkage. Then, the linearized form of objective equation is proposed. This makes contour matching easier to implement. Finally, the multigrid method is used to speed up the convergence.

关键词： Contour matching curvature wavelet transform multigrid method

USING wavelet transform TO STUDY THELIPSCHITZ LOCAL SINGULAR EXPONENTIN WALL TURBULENCE

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Applied Mathematics and Mechanics(English Edition) 1998年第10期19卷 983-990页

作者：姜楠王振东舒玮 Department of Mechanics Tianjin University Tianjin Laboratory for Nonlinear Mechanics of Continuous Media Institute of Mechanics Academia Sinica Beijing P. R. China

In this paper, wavelet,transform is introduced to study the Lipschitz local singular exponent for characterising the local singularity behavior of fluctuating velocity in wall turbulence. I, is found that the local singular exponent is negative when the ejections and sweeps of coherent structures occur in a turbulent boundary layer.

关键词： wavelet transform coherent structure Lipschitz local singular exponent

wavelet transform and Image Processing

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Systems Science and Systems Engineering 1993年第4期3卷 377-384页

作者： CHENG Daizhan Dept. of Math., Rowan College of New Jersey, Glassboro, NJ 08028

This paper presents systematically a method for image compression/decompression via wavelet transform. It consists of filter, quantization and Huffman coding etc.. Different methods have been compared. Finally,some su... 详细信息

关键词： image processing wavelet transform quantization coding.