- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Investigation of Remote Sensing Image Fusion Strategy Applying PCA to Wavelet Packet Analysis Based on IHS Transform
摘要： Further exploration of wavelet packet analysis (WPA) in the area of image fusion has been a hot topic. It is a strategy to combine WPA with such other transforms as intensity–hue–saturation (IHS), principle component analysis (PCA) for image fusion between the panchromatic (PAN) and the multispectral (MS) image. The paper puts forward a distinct fusion method. Its main idea can be stated as three steps. Firstly, intensity component is derived from IHS model of the image after an MS image is transformed from RGB to IHS. Secondly, intensity component and a matched PAN image are decomposed by WPA at the second scale, respectively. The innovational concept with two aspects is applying PCA theory to merge wavelet packet coefficients. One is to detect edge and produce self-adaptive weighted ratios for low-frequency band. The other is to yield another weighted coefficients for high-frequency bands based on standard deviation. Lastly, the new intensity component created by implementing inverse WPA, matching with hue and saturation reserved, makes up a color composition. A fused image is produced when carrying out transformation from IHS to RGB for the composition. It turns out that the presented fusion strategy is effective with experiments.
关键词： Intensity–hue–saturation (IHS),Image fusion,PCA-based fusion rule,Principle component analysis (PCA),Wavelet packet analysis (WPA)
更新于2025-09-23 15:23:52
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Fabrication and characterization of VOC sensor array based on SnO2 and ZnO nanoparticles functionalized by metalloporphyrins
摘要： A volatile organic compound (VOC) sensor array based on metal oxide nanoparticles (MOX NPs) functionalized by metalloporphyrins (MPPs) was demonstrated. The VOC sensor array was composed of four single sensors based on SnO2 NPs/cobalt-porphyrin, SnO2 NPs/zinc-porphyrin, SnO2 NPs/nickel-porphyrin and ZnO NPs/cobalt-porphyrin. The MOX NP/MPP-based sensors were fabricated by drop-casting the MOX NPs dispersion and MPPs solution onto a MEMS platform. The fabricated sensor successfully detected toluene at a concentration as low as 20 ppb, which is below the limit detection concentration of previously reported porphyrin-based VOC sensor arrays. We also confirmed the selectivity between benzene, toluene, ethylbenzene, and xylene (BTEX) by using principal component analysis in contrast to previous studies on MOX/MPP-based sensor. BTEX was classified from 1 to 9 ppm at a resolution of 2 ppm, and the sensor array showed stable performance even after considerable impact.
关键词： Gas sensor array,Porphyrin,Principle component analysis,Metal oxide,Volatile organic compound
更新于2025-09-23 15:22:29
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[IEEE 2019 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - Guangzhou, China (2019.5.19-2019.5.22)] 2019 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - Ultrawideband Tightly Coupled Dipole Array with 70?° Scanning for Millimeter-Wave Bands
摘要： Cloud computing enables customers with limited computational resources to outsource their huge computation workloads to the cloud with massive computational power. However, in order to utilize this computing paradigm, it presents various challenges that need to be addressed, especially security. As eigen-decomposition (ED) and singular value decomposition (SVD) of a matrix are widely applied in engineering tasks, we are motivated to design secure, correct, and efficient protocols for outsourcing the ED and SVD of a matrix to a malicious cloud in this paper. In order to achieve security, we employ efficient privacy-preserving transformations to protect both the input and output privacy. In order to check the correctness of the result returned from the cloud, an efficient verification algorithm is employed. A computational complexity analysis shows that our protocols are highly efficient. We also introduce an outsourcing principle component analysis as an application of our two proposed protocols.
关键词： eigen-decomposition,principle component analysis,singular value decomposition,Cloud computing,secure outsourcing
更新于2025-09-23 15:21:01
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Artificial tailored catalytic activity for identification of 6 kinds of volatile organic compounds via the light-regulated electrochemical reaction
摘要： Light-regulated electrochemical reaction is confirmed to be useful to improve the classification efficiency. However, the use of different photoactive sensing materials results in time-consuming for exploring well-designed materials, besides, the light-regulated electrochemical reaction only improved the classification feature while didn't bring essential difference in the distinguish capability yet. Herein, a zirconia-based electrochemical sensor array comprised of 3 types of ZnO/In2O3 composite sensing materials is fabricated. After illumination, significantly enhancement is witnessed for the response magnitude and detection limit. Additionally, the response signal of the sensor array to part of the examined volatile organic compounds (VOCs) is selectively enhanced and 3 more disparate response patterns are generated. Through inputting all the response patterns into principle component analysis (PCA) software, 6 kinds of concerned VOCs have been fully classified. Conclusively, with utilizing sensing materials with similar composition, the fabrication process of the sensor array can be simplified. Particularly, after exposure to illumination the sensor array consisting of limited photoactive sensing materials (e.g. 3 kinds of materials) can identify even more number of gases (e.g. 6 types of VOCs). We anticipate these promising results shed light on the bright future of designing compact sensing devices for progressively smarter monitoring of concerned gas species.
关键词： Principle component analysis,Light-regulated electrochemical reaction,Volatile organic compounds,Response patterns,Artificial tailored catalytic activity,Zirconia-based sensor array
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE Power & Energy Society General Meeting (PESGM) - Atlanta, GA, USA (2019.8.4-2019.8.8)] 2019 IEEE Power & Energy Society General Meeting (PESGM) - A State-Space Dynamic Model for Photovoltaic Systems with Full Ancillary Services Support
摘要： A fast search method based on principle component analysis (PCA) is proposed to search codewords using vector quantization (VQ) codebooks obtained by PCA with Linde–Buzo–Gray (LBG) algorithms. The PCA sorts vectors of a test image and codewords of a PCA-LBG-based VQ codebook. The first search starts from the first codeword in the sorted codebook, and the next search starts from the previous best-matching codeword position in the sorted codebook. Both forward and backward searches are performed within the set search range until the best-matching codewords for all vectors of the test image are found in a sorted codebook. Because PCA efficiently distinguishes both test image vectors and codebook codewords, the proposed PCA-based fast search method outperforms the conventional algorithms in a codebook search. In particular, the experimental results show that, by using PCA-LBG-based VQ codebooks, the proposed PCA-based fast search method outperforms other methods in terms of peak signal-to-noise ratio for the compressed image, number of codewords searched, and runtime.
关键词： codebook,fast search,principle component analysis,Vector quantization
更新于2025-09-19 17:13:59
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[IEEE 2019 Workshop on Recent Advances in Photonics (WRAP) - Guwahati, India (2019.12.13-2019.12.14)] 2019 Workshop on Recent Advances in Photonics (WRAP) - Spectrum Analysis of Ytterbium-Doped Hybrid Mode-Locked Fiber Laser
摘要： Cloud computing enables customers with limited computational resources to outsource their huge computation workloads to the cloud with massive computational power. However, in order to utilize this computing paradigm, it presents various challenges that need to be addressed, especially security. As eigen-decomposition (ED) and singular value decomposition (SVD) of a matrix are widely applied in engineering tasks, we are motivated to design secure, correct, and efficient protocols for outsourcing the ED and SVD of a matrix to a malicious cloud in this paper. In order to achieve security, we employ efficient privacy-preserving transformations to protect both the input and output privacy. In order to check the correctness of the result returned from the cloud, an efficient verification algorithm is employed. A computational complexity analysis shows that our protocols are highly efficient. We also introduce an outsourcing principle component analysis as an application of our two proposed protocols.
关键词： eigen-decomposition,principle component analysis,singular value decomposition,Cloud computing,secure outsourcing
更新于2025-09-19 17:13:59
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Coupled-Line-Based <i>Ka</i> -Band CMOS Power Dividers
摘要： Cloud computing enables customers with limited computational resources to outsource their huge computation workloads to the cloud with massive computational power. However, in order to utilize this computing paradigm, it presents various challenges that need to be addressed, especially security. As eigen-decomposition (ED) and singular value decomposition (SVD) of a matrix are widely applied in engineering tasks, we are motivated to design secure, correct, and efficient protocols for outsourcing the ED and SVD of a matrix to a malicious cloud in this paper. In order to achieve security, we employ efficient privacy-preserving transformations to protect both the input and output privacy. In order to check the correctness of the result returned from the cloud, an efficient verification algorithm is employed. A computational complexity analysis shows that our protocols are highly efficient. We also introduce an outsourcing principle component analysis as an application of our two proposed protocols.
关键词： eigen-decomposition,principle component analysis,singular value decomposition,Cloud computing,secure outsourcing
更新于2025-09-19 17:13:59
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AIP Conference Proceedings [AIP Publishing PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON BIOSCIENCES AND MEDICAL ENGINEERING (ICBME2019): Towards innovative research and cross-disciplinary collaborations - Bali, Indonesia (11–12 April 2019)] PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON BIOSCIENCES AND MEDICAL ENGINEERING (ICBME2019): Towards innovative research and cross-disciplinary collaborations - Laser-induced breakdown spectroscopy (LIBS) for printing ink analysis coupled with principle component analysis (PCA)
摘要： Laser-induced breakdown spectroscopy (LIBS) has been applied to perform elemental analysis of printing ink samples. Samples of black printing inks from three types of printers viz. inkjet, laser-jet, and photocopier (three different brands for each type) and one control sample (blank white A4 paper) were analysed under optimised conditions. Results revealed that the LIBS method when coupled with PCA was able to provide discriminative evidence on elemental differences among all the different printing inks. Considering its time and cost effectiveness as well as requiring only minute amount of sample with no sample pre-treatment steps, the combination of LIBS and PCA may prove useful for forensic questioned document practical caseworks.
关键词： forensic questioned document,Laser-induced breakdown spectroscopy,principle component analysis,PCA,printing ink analysis,LIBS
更新于2025-09-16 10:30:52
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A novel intensity-based multi-level classification approach for coronary plaque characterization in intravascular ultrasound images
摘要： Background: Intravascular ultrasound (IVUS) is a commonly used diagnostic imaging method for coronary artery disease. Virtual histology (VH) characterizes the plaque components into fibrous tissue (FT), fibro-fatty tissue (FFT), necrotic core (NC), or dense calcium (DC). However, VH can obtain only a single-frame image in one cardiac cycle, and specific software is needed to obtain the radio frequency data. This study proposed a novel intensity-based multi-level classification model for plaque characterization. Methods: The plaque-containing regions between the intima and the media-adventitia were segmented manually for all IVUS frames. A total of 54 features including first order statistics, grey level co-occurrence matrix, Law’s energy measures, extended grey level run length matrix, intensity, and local binary pattern were estimated from the plaque-containing regions. After feature extraction, optimal features were selected using principle component analysis (PCA), and these were utilized as the input for the classification models. Plaque components were classified into FT, FFT, NC, or DC using an intensity-based multi-level classification model consisting of three different nets. Net 1 differentiated low-intensity components into FT/FFT and NC/DC groups. Then, net 2 subsequently divided FT/FFT into FT or FFT, whereas the remainder and high-intensity components were classified into NC or DC via net 3. To improve classification accuracy, each net utilized three different input features obtained by PCA. Classification performance was evaluated in terms of sensitivity, specificity, accuracy, and receiver operating characteristic curve. Results: Quantitative results indicated that the proposed method showed significantly high classification accuracy for all tissue types. The classifiers had classification accuracies of 85.1%, 71.9%, and 77.2%, respectively, and the areas under the curve were 0.845, 0.704, and 0.783. In particular, the proposed method achieved relatively high sensitivity (82.0%) and specificity (87.1%) for differentiating between the FT/FFT and NC/DC groups. Conclusions: These results confirmed the clinical applicability of the proposed approach for IVUS-based tissue characterization.
关键词： Intravascular ultrasound,Intensity-based multi-level classification,Texture features,Plaque characterization,Principle component analysis
更新于2025-09-11 14:15:04
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Innovative Multi Pcnn Based Network for Green Area Monitoring - Identification and Description of Nearly Indistinguishable Areas - In Hyperspectral Satellite Images
摘要： The paper presents an original neural network approach for region of interest detection and classification in multi-spectral satellite images. The proposed method uses a sequence of Pulse Coupled Neural Networks that identifies plausible regions of interest. These regions are passed to a dimension reduction algorithm, Principle Component Analysis, in order to generate the input data for a Support Vector Machine classifier, that validates the data. The algorithm's parameters are optimized using a Genetic Algorithm. The algorithm is designed to distinguish regions that are extremely similar, such as parks in a city that has entire districts made up of houses with yards. The algorithm has been tested on images provided by the Sentinel-2 satellite, and it proved that it can recall 76.85% of the pixels marked as park in the ground truth data, which was obtained from OpenStreetMap.
关键词： Genetic Algorithm (GA),Pulse Coupled Neural Network (PCNN),Principle Component Analysis (PCA),Support Vector Machine (SVM)
更新于2025-09-10 09:29:36