- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Low-rank and sparse matrix decomposition with background position estimation for hyperspectral anomaly detection
摘要： Hyperspectral anomaly detection (AD) has attracted much attention over the last 20 years. It distinguishes pixels with significant spectral differences from the background without any prior knowledge. The low-rank and sparse matrix decomposition (LRaSMD)-based detector has been applied to AD, where the anomaly value is measured by Euclidean distance based on the sparse component. However, the background interference in sparse component seriously increases the false alarm rate and influences the detection of real anomalies. In this paper, a novel AD method based on LRaSMD and background position estimation is proposed, which aims to suppress background interference in the sparse component for a better separation between background and anomalies. Firstly, the original sparse matrix is obtained using the traditional LRaSMD method. Secondly, the abundance maps are constructed by the sequential maximum angel convex cone (SMACC) endmember extraction model. Thirdly, considering that the anomalies occupy only a few pixels with a low probability, the coordinate positions of background pixels are estimated through these abundance maps. Finally, the spectra corresponding to these positions in the original sparse matrix are replaced with zero vectors, and the final anomaly value is calculated based on the improved sparse matrix. The proposed method achieves an outstanding performance by considering both the spectral and spatial characteristics of anomalies. Experimental results on synthetic and real-world hyperspectral datasets demonstrate the superiority of the proposed method compared with several state-of-the-art AD detectors.
关键词： Anomaly detection,Background estimation,Low-rank and sparse matrix decomposition,Hyperspectral imagery,Endmember extraction
更新于2025-09-23 15:23:52
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A profile error evaluation method for freeform surface measured by sweep scanning on CMM
摘要： Coordinate measuring machines (CMMs) are widely used in evaluating the profile error of the freeform surfaces. Traditional trigger probes are inefficient at collecting large scale measurement sets. A CMM equipped with a sweep scanning probe dramatically improves the efficiency of inspection. However, the large scale data obtained by scanning is challenging for most existing profile error evaluation methods, which are based on iterative algorithms. This paper proposes an efficient and accurate method to evaluate the profile error of freeform surfaces. To simultaneously simplify the calculation and retain the accuracy of evaluation, a new method to extract key points from scanning data set is presented. First, the key points are defined as those measured points with regional outstanding deviations from the design surface. Second, wavelet decomposition is utilized to decompose the curves formed by the deviations of the measured points in the scanning data set, and the key points are extracted according to the decomposition results. In addition, the key points set, as a representation of the scanning data, are evaluated using Sequential Quadratic Programming (SQP) algorithm. Finally, a simulation example and an actual machined part are used to test the proposed evaluation method. The results prove that the proposed method is both accurate and efficient.
关键词： Key points extraction,Profile error evaluation,Freeform surface,Wavelet decomposition,Sweep scanning
更新于2025-09-23 15:23:52
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Disentangling topographic contributions to near-field scanning microwave microscopy images
摘要： We develop empirical models to predict the contribution of topographic variations in a sample to near-field scanning probe microwave microscopy (NSMM) images. In particular, we focus on |S11| images of a thin Perovskite photovoltaic material and a GaN nanowire. The difference between the measured NSMM image and this prediction is our estimate of the contribution of material property variations to the measured image. Prediction model parameters are determined from either a reference sample that is nearly free of material property variations or directly from the sample of interest. The parameters of the prediction model are determined by robust linear regression so as to minimize the effect of material property variations on results. For the case where the parameters are determined from the reference sample, the prediction is adjusted to account for instrument drift effects. Our statistical approach is fully empirical and thus complementary to current approaches based on physical models that are often overly simplistic.
关键词： Near-field scanning probe microwave microscopy,Signal extraction,GaN nanowire,Statistical methods,Perovskite materials,Atomic force microscopy
更新于2025-09-23 15:23:52
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Effect of the Photodynamic Therapy Applications with Potent Microalgae Constituents on Several Types of Tumor
摘要： Background: In recent years, microalgae (MA) have attracted much interest considering their possible therapeutic application. They contain active natural compounds or derivatives (extracts, pure or chemically modified compounds) that have increasing applications in the pharmaceutical industry. Methods: The present study aims to examine microalgae for new photosensitizers, with a potential to be used in the light-associated treatment of tumors. Semi-purified extracts of several microalgae strains were evaluated as photosensitizers for photodynamic therapy (PDT) applications. Four tumor cell lines (A549, LNCap, MCF-7, and MDA-MB 435) were used to assess 34 samples extracted by three methods: cellulase enzyme, lysozyme enzyme and ultra-sonication. The fluorescence measurements and the recorded images alongside the spectral intensities between 650–800 nm wavelengths provided characteristic features to some of the contents of the examined extracts. Results: Several microalgae constituents activated by blue light (BL), red light (RL) or both (in sequence) exhibited significant effects on the viability of the tumor cell lines, decreasing it as much as 95% for certain MA constituents. Majority of the MA constituents showed a higher phototoxicity after exposure to both blue and red lights than the photo-induced toxicity when exposed to a single light source. The viability of the tumor cells exhibited the dose dependent response with the MA constituents. Conclusion: The results clearly showed that MA constituents are potential photosensitizers that have a significant photo-damage effects on the tested cancer cells.
关键词： Anticancer agent,Microalgae,Enzymatic extraction,Photodynamic therapy,Photosensitizers
更新于2025-09-23 15:23:52
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A novel parameter derived from photoplethysmographic pulse wave to distinguish preeclampsia from non-preeclampsia
摘要： Objective: To describe the comparative hierarchical area ratio (CHAR), a novel parameter derived from the photoplethysmographic (PPG) pulse wave and differences in CHAR values in parturients with and without preeclampsia (PE). Methods: A total of 59 parturients (37 without and 22 with PE) was conducted at the Women’s Hospital of Zhejiang University in Hangzhou, China. We calculated the CHAR values derived from the PPG pulse wave and compared them in parturients with and without PE. Result: The values of CHAR derived from the parturients with PE were lower compared to those without PE (p<0.01). The ROC analysis indicated that the best threshold for the mean value of CHAR was 7.92 to predict PE with a sensitivity of 86.4% and a specificity of 87.1%, while the threshold for the standard deviation of CHAR was 0.76 with a sensitivity of 77.3% and a specificity of 77.4%. The area under the curve (AUC) was 0.91 for mean value of CHAR while 0.78 for standard deviation of CHAR. Meanwhile, a contrast of AUC between CHAR and the former parameter we proposed showed CHAR had better performance in distinguishing PE (0.908 over 0.615, p<0.01). Conclusion: The novel parameter, CHAR, derived from PPG pulse wave differs in parturients with and without PE with high sensitivity and specificity, suggesting that the CHAR might be an effective tool in differentiating the presence of PE.
关键词： Morphology,Characteristics Extraction,Comparative Hierarchical Area Ratio (CHAR),Photoplethysmographic pulse wave,Preeclampsia
更新于2025-09-23 15:23:52
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Image based leaf segmentation and counting in rosette plants
摘要： This paper proposes an efficient method to extract the leaf region and count the number of leaves in digital plant images. The plant image analysis plays a significant role in viable and productive agriculture. It is used to record the plant growth, plant yield, chlorophyll fluorescence, plant width and tallness, leaf area, etc. frequently and accurately. Plant growth is a major character to be analyzed among these plant characters and it directly depends on the number of leaves in the plants. In this paper, a new method is presented for leaf region extraction from plant images and counting the number of leaves. The proposed method has three steps. The first step involves a new statistical based technique for image enhancement. The second step involves in the extraction of leaf region in plant image using a graph based method. The third step involves in counting the number of leaves in the plant image by applying Circular Hough Transform (CHT). The proposed work has been experimented on benchmark datasets of Leaf Segmentation Challenge (LSC). The proposed method achieves the segmentation accuracy of 95.4% and it also achieves the counting accuracy of (cid:1)0.7 (DiC) and 2.3 (|DiC|) for datasets (A1, A2 and A3), which are better than the state-of-the-art methods.
关键词： Leaf count,Plant image analysis,Plant phenotyping,Leaf region extraction
更新于2025-09-23 15:23:52
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Distributed Small-signal Equivalent Circuit Model and Parameter Extraction for SiGe HBT
摘要： In this paper, we present an improved high frequency small-signal distributed model for SiGe HBTs under forward-active mode based on the transmission line theory. The distributed nature of the transistor structure is taken into account in the proposed model. The single SiGe HBT is considered to be a cascade of many infinitesimal transistors, connected with the intrinsic base resistance. The closed-form solutions of admittance parameters for the distributed model are derived by solving the transmission line equation. With reasonable approximation and simplification, the model parameters are then directly extracted based on the nonlinear rational function fitting. The new improved distributed model and parameter extraction technique are validated with a 1×1.2×30 μm2 SiGe HBT from 100 MHz to 20.89 GHz. The simulated S-parameters in the proposed transmission line model are in close agreement with the measured data, and the frequency characteristics of the transistors are well predicted.
关键词： parameter extraction,rational function fitting,transmission line,SiGe HBT,Device modeling,small-signal model
更新于2025-09-23 15:23:52
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[IEEE 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT) - Kannur (2018.3.23-2018.3.24)] 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT) - Identification of Melanoma in Dermoscopy Images Using Image Processing Algorithms
摘要： Skin cancer is the most common of all human cancers and is always misunderstood with other kind of skin diseases, so accurate early detection of skin cancer is essential. The main objective of this paper is to segment the lesion and identify melanoma from dermoscopy images. A total of 170 dermoscopy images are used in this research. Firstly, the input images are enhanced for better processing then, the lesion portion is segmented from the enhanced image by two methods 1.Otsu thresholding 2.Morphological operations. The descriptive features are extracted from the segmented lesion. The extracted feature values are used to compute the Total Dermatascopy Score (TDS), which is used to find the presence or absence of melanoma in dermoscopy images. Classification accuracy is calculated to assess the performance of the proposed algorithm.
关键词： Dermoscopy,Segmentation,Total Dermatoscopy Score(TDS),Feature Extraction,Melanoma,Skin cancer
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Sparse and Smooth Feature Extraction for Hyperspectral Imagery
摘要： In this paper, a hyperspectral feature extraction (FE) method called sparse and smooth low-rank analysis (SSLRA) is proposed. First, we propose a new low-rank model for hyperspectral images (HSIs). In the new model, HSI is decomposed into smooth and sparse unknown features which live in an unknown orthogonal subspace. Then, the sparse and smooth features are simultaneously estimated using a non-convex constrained penalized cost function. In the experiments, SSLRA is applied on a real HSI and the smooth features extracted are used for the HSI classification. The results confirm improvements in classification accuracies compared to state-of-the-art FE methods.
关键词： regularization,Feature extraction,sparsity,low-rank model,total variation,hyperspectral image
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Extraction of Structural and Mineralogical Features from Hyperspectral Drill-Core Scans
摘要： For vein hosted mineralization such as encountered in porphyry systems, the documentation of the main alteration assemblages associated with specific vein generations is essential in understanding the geometry of the mineralized body. Hence, mineralogical and structural information are highly relevant for characterizing the system. In this paper, we present an approach for the extraction of both mineralogical and structural information from hyperspectral scans. We propose a parallel framework which includes a typical mineral mapping technique for the extraction of mineralogical information as well as a ridge detection method, for the extraction of veins, applied on mineral abundance maps. In the proposed framework, the abundance maps are obtained from hyperspectral VNIR-SWIR drill-core scans using a linear spectral unmixing technique. Drill cores hosting porphyry stockwork type mineralization are used for the evaluation of the proposed technique and the experimental results show that the method offers a tool for accurately characterizing the mineralized body.
关键词： Core scanning,feature extraction,hyperspectral imaging,mineral mapping,image segmentation
更新于2025-09-23 15:22:29