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IEEE International Geoscience and Remote Sensing Symposium

作者： Xiangkun Zhang Zelong Shao Jiawei Ren Yingsong Li Jingshan Jiang Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China CAS National Space Science Center Beijing China

The small-size unmanned aerial vehicle (UAv) is being used widely in many fields, especially in surveying, mapping and remote sensing. Due to the platform's size and load ability, its payload is strictly limited. Synthetic aperture radar (SAR) is a kind of microwave imaging instrument with high performance under all weather, day and night conditions. Highly miniaturized SAR can satisfy the requirement of observation on small UAv. Frequency modulation continuous wave (FMCW) technology provides a way for small volume, low cost, high reliability and high resolution SAR. FMCW SAR transmits frequency modulated signal continuously. This reduces the peak power, which is the important factor determining the size and cost of SAR. Meanwhile, due to transmitting and receiving signals simultaneously, increasing the isolation between the transmitter and receiver becomes associated problem. Two separated antennas solve the problem partly. There is another problem in processing algorithm. Long duration of signal makes the assumption of stop and go model ineffective. Frequency scaling algorithm has to be chosen to correct the phase variation during one period of frequency sweep. Procedure of development for prototype and practical systems and verification experiments are shown in this paper. The results of experiments with such radars prove the expected performance.

关键词： Synthetic aperture radar Radar imaging Imaging image resolution Prototypes Signal processing algorithms

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Managing Diseases Thru' Asclepios: An Agile Information Exploitation Framework

Managing Diseases Thru' Asclepios: An Agile Information Expl...

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IST-Africa Week Conference (IST-Africa)

作者： Narasimhan, v. Lakshmi Univ Botswana Gaborone Botswana

ISBN: (纸本)9781538638378

This paper describes the development of an open-source information system, called Asclepios, which manages a plethora of information on communicable diseases in an agile manner. Asclepios exploits information from multiple databases from both open sources (Third Party) and Second party sources. A variety of tools are available in Asclepios to perform extensive processing of numeric and texts (along with some image and video processing) so that trend information can be gleaned on various communicable diseases. The Asclepios architecture draws together a confluence of technologies and industrial standards such as: cloud computing, metadata, ontology generation and management, artificial intelligence, pattern recognition, decision support system, data mining and systems engineering. Because of the use of Component Based Software Engineering (CBSE) methodology for its design, the architecture is scalable, its components replaceable dynamically and configured for the requirements of a given application. The underlying architecture of Asclepios is therefore horizontal, but it has an ability to support several verticals as epidemiology, pharmacology and other fields easily. The application of Asclepios is wide ranging - from military to Government through to medical and tourism and pharmaceuticals. Further, Asclepios-like applications are very much needed in most Third world countries, including all countries in Africa, as it can significantly enhance the health, safety and well-being of people.

关键词： Agile information exploitation Communicable diseases Shallow text processing Cloud computing Metadata generation Ontology management Pattern recognition algorithms

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Studying Fish Near Ocean Energy Devices Using Underwater video

Studying Fish Near Ocean Energy Devices Using Underwater Vid...

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Conference on OCEANS

作者： Matzner, S. Hull, R. E. Harker-Klimes, G. Cullinan, v., I Pacific Northwest Natl Lab Elect & Measurement Syst Sequim WA 98382 USA Pacific Northwest Natl Lab Coastal Sci Seattle WA USA

ISBN: (纸本)9780692946909

The effects of marine and instream energy devices on fish populations are not well-understood, and studying the behavior of fish around these devices is challenging. To address this problem, we have evaluated algorithms to automatically detect fish in underwater video and propose a semi-automated method for ocean and river energy device ecological monitoring. The key contributions of this work are the demonstration of a background subtraction algorithm that detected 87% of human-identified fish events and is suitable for use in a real-time system to reduce data volume, and the demonstration of a statistical model to classify detections as fish or not fish that achieved a correct classification rate of 85% overall and 92% for detections larger than 5 pixels. This automated processing would significantly reduce labor time and costs, compared to current monitoring methods. Specific recommendations for underwater video acquisition to better facilitate automated processing are given. The proposed automated processing and recommendations will help energy developers put effective monitoring systems in place, and could lead to a standard approach that advances the scientific understanding of the ecological impacts of ocean and river energy devices.

关键词： object detection image analysis machine vision marine technology underwater technology

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Spectroscopic super-resolution fluorescence cell imaging using ultra-small Ge quantum dots

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OPTICS EXPRESS 2017年第4期25卷 4240-4253页

作者： Song, Mingying Karatutlu, Ali Ali, Isma Ersoy, Osman Zhou, Yun Yang, Yongxin Zhang, Yuanpeng Little, William R. Wheeler, Ann P. Sapelkin, Andrei v. Queen Mary Univ London Sch Phys & Astron London E1 4NS England Bursa Orhangazi Univ Elect & Elect Engn TR-16310 Bursa Turkey Kings Coll London Nikon Imaging Ctr London WC2R 2LS England Queen Mary Univ London Sch Elect Engn & Comp Sci London E1 4NS England Univ Edinburgh Inst Genet & Mol Med Edinburgh EH4 2XU Midlothian Scotland Edinburgh Super Resolut Interdisciplinary Consort Edinburgh EH4 2XU Midlothian Scotland

We demonstrate a spectroscopic imaging based super-resolution approach by separating the overlapping diffraction spots into several detectors during a single scanning period and taking advantage of the size-dependent emission wavelength in nanoparticles. This approach has been tested using off-the-shelf quantum dots (Invitrogen Qdot) and in-house novel ultra-small (similar to 3 nm) Ge QDs. Furthermore, we developed a method-specific Gaussian fitting and maximum likelihood estimation based on a Matlab algorithm for fast QD localisation. This methodology results in a three-fold improvement in the number of localised QDs compared to non-spectroscopic images. With the addition of advanced ultrasmall Ge probes, the number can be improved even further, giving at least 1.5 times improvement when compared to Qdots. Using a standard scanning confocal microscope we achieved a data acquisition rate of 200 ms per image frame. This is an improvement on single molecule localisation super-resolution microscopy where repeated image capture limits the imaging speed, and the size of fluorescence probes limits the possible theoretical localisation resolution. We show that our spectral deconvolution approach has a potential to deliver data acquisition rates on the ms scale thus providing super-resolution in live systems. Published by The Optical Society

关键词： image processing algorithms Live cell imaging Optical imaging Structured illumination microscopy Three dimensional imaging Ultraviolet radiation

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FRACTAL SPECKLE image ANALYSIS FOR SURFACE CHARACTERIZATION OF AEROSPACE STRUCTURES 5

FRACTAL SPECKLE IMAGE ANALYSIS FOR SURFACE CHARACTERIZATION ...

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5th International Conference on Optical and Photonics Engineering

作者： Haridas, Aswin Crivoi, Alexandru Prabhathan, P. Chan, Kelvin Murukeshan, v. M. Nanyang Technol Univ Rolls Royce NTU Corp Lab 65 Nanyang Dr Singapore 637460 Singapore Nanyang Technol Univ Sch Mech & Aerosp Engn 50 Nanyang Dr Singapore 639798 Singapore Rolls Royce Singapore 6 Seletar Aerosp Rise Singapore 797575 Singapore

ISBN: (数字)9781510613737

ISBN: (纸本)9781510613737;9781510613720

Surface characterization of the working components has always been a subject of interest among researchers and industry specialists. Especially in the aerospace industry where the aerodynamic capabilities are largely altered by the surface quality of the component of interest, there remains an extensive need for developing systems for effectively characterizing the surface quality. To realize an optical based non-contact and an in-line surface roughness measurement system, it is essential to understand the relationship between the quality of the surface and statistical parameter of the reflected speckles. The range of the measurement system being proportional to the wavelength of light used makes the analysis fundamentally important in order to understand the properties of speckles at a different wavelength. In this context, this paper examines the nature of the formed IR speckles from three different diffusers by analyzing their raw structure. image processing algorithms that are developed study the different parameters of the 8-bit binary speckles, namely, the fractal property and number of connecting components. The paper also discusses the future work direction on relating the proposed analysis to derive the algorithm required for evaluating the surface finish parameters.

关键词： image processing Fractal dimension Infra-Red Surface Roughness

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Post-traumatic Epilepsy in rat's: An algorithm for detection of suspicious EEG activity 13

Post-traumatic Epilepsy in rat's: An algorithm for detection...

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13th International Conference on Signal-image Technology and Internet-Based systems (SITIS)

作者： Kershner, Ivan A. Obukhov, Yury v. Komoltsev, Ilya G. RAS Kotelnikov Inst Radio Engn & Elect Mokhovaya 11-7 Moscow 125009 Russia RAS Inst Higher Nervous Activ & Neurophysiol IHNA& NPh RAS Butlerova 5A Moscow Russia

ISBN: (纸本)9781538642832

Due to the fact that there are problems in neurophysiological research on post-traumatic epilepsy in order to find sleep spindles and epileptiform discharges in long-term (day or more) recordings of electroencephalography (EEG) there is a need for algorithms for automatic detection of suspicious EEG activity (we call as suspicious activity any EEG activity that differs from the background activity). There are many methods of signal processing. The most common and straightforward are the methods of transition from the temporal representation of the signal to the time-frequency representation. One of them is the wavelet transform. For the wavelet spectrograms, the ridges of the wavelet spectrograms are calculated. Method of detecting the suspicious activity involves an analysis of points of the ridges. The spectrogram of ridge points are calculated, after which the points of the ridge are divided into two groups: those that relate to the background activities and those that relate to suspicious activity. Suspicious activity that does not meet the requirements of neuroscientists is eliminated.

关键词： post-traumatic epilepsy EEG rat wavelet transform suspicious activity ridge detection

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Sentinel-2 MultiSpectral Instrument (MSI) data processing for aquatic science applications: Demonstrations and validations

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REMOTE SENSING OF ENvIRONMENT 2017年 201卷 47-56页

作者： Pahlevan, N. Sarkar, S. Franz, B. A. Balasubramanian, S. v. He, J. NASA Goddard Space Flight Ctr 8800 Greenbelt Rd Greenbelt MD 20771 USA Sci Syst & Applicat Inc 10210 Greenbelt RdSuite 600 Lanham MD 20706 USA Univ Maryland Dept Geog Sci College Pk MD 20740 USA

The European Space Agency's Sentinel-2A mission with the MultiSpectral Instrument (MSI) onboard was launched in 2015, initiating a new era in high-to-moderate-resolution (i.e., 10 to 60 m) imaging of Earth's resources. This manuscript describes the implementations of MSI processing into the SeaWiFS Data Analysis System (SeaDAS) and provides qualitative and quantitative analyses of remote sensing reflectance products (Rrs), which are essential in the retrievals of near-surface concentrations of water constituents in aquatic systems. In situ validations and intercomparisons of MSI-derived 11 products with those derived from Landsat-8's Operational Land imager (OLI) both indicated reasonable products in coastal/inland waters. Following vicarious calibrations using reference in situ water-leaving radiances, the overall absolute relative differences and the root mean squared differences (RMSD) found for the matchup analyses were, < 7% and < 0.0012 1/sr, respectively, for the blue and green bands. With preliminary indications of consistency with the OLI products and very good agreements with in situ data, a time-series plot of total suspended solids (TSS) product derived from both missions was produced and analyzed for an inland system. It is surmised that frequent moderate-to-high resolution R products from the combined Sentinel-2A (and 13) and Landsat-8 missions are now available to the science/user community for developing algorithms suited for coastal/inland waters. Nonetheless, further research needs to be dedicated to a) improving atmospheric corrections over bodies of waters rich in dissolved organic matter or suspended particles, b) mitigating the impact of haze-or sea surface-reflected solar radiations at low solar zenith angles, and c) minimizing image artifacts to maximize the use of multi-mission products.

关键词： Sentinel-2A Atmospheric correction Aquatic science applications Calibration/validation

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Proposal of Effective Orthogonal and Hexagonal Hierarchical Structures for Disc Queries

Proposal of Effective Orthogonal and Hexagonal Hierarchical ...

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International Conference on Cybernetics, Robotics and Control (CRC)

作者： vojtěch Uher Petr Gajdoš václav Snášel Department of Computer Science VŠB-Technical University of Ostrava Ostrava Czech Republic

ISBN: (纸本)9781538677391

The Fixed-Radius Nearest Neighbors (FRNN) query is a common task in scientific areas dealing with multidimensional point clouds (PCs) such as computer graphics, image processing, geographic information systems, machine learning and pattern recognition. We especially focus on 2D points in this paper. The FRNN means search all the points within defined radius for tasks when local properties of data are crucial. As this procedure is time consuming, an effective accelerating structure indexing the points is required. The standard methods are based on the orthogonal grids subdividing the space into uniform cells or hierarchies of orthogonal grids. However, several papers highlight the regular hexagonal grids for their superior theoretical metrics, e.g. better coverage of query discs, uniform distance to all six neighbors or lower number of passed cells. This paper provides a comparison of effectiveness of orthogonal and hexagonal hierarchies and traditional algorithms for FRNN disc queries. To do this, we propose a novel hierarchical method based on the hexagonal space-filling curve called the Node-Gosper curve which defines the hierarchical location of points in the hexagonal grids and their linear order. This method is tested with similar structure based on the orthogonal Z-order curve to show the real features of both approaches in practice.

关键词： Three-dimensional displays vegetation Two dimensional displays Fractals Task analysis Shape Standards

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Convolutional Neural Network Based Localized Classification of Uterine Cervical Cancer Digital Histology images

Convolutional Neural Network Based Localized Classification ...

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Complex Adaptive systems Conference on Engineering Cyber Physical systems (CAS)

作者： Almubarak, Haidar A. Stanley, R. Joe Long, Rodney Antani, Sameer Thoma, George Zuna, Rosemary Frazier, Shelliane R. Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65401 USA NIH Lister Hill Nationa Ctr Biomed Commun DHHS Natl Lib Med Bldg 10 Bethesda MD 20892 USA Univ Oklahoma Hlth Sci Ctr Dept Pathol Oklahoma City OK 73117 USA Univ Missouri Hosp & Clin Dept Surg Pathol Columbia MO 65202 USA

In previous research, we introduced an automated localized, fusion-based algorithm to classify squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN). The approach partitioned the epithelium into 10 segments. image processing and machine vision algorithms were used to extract features from each segment. The features were then used to classify the segment and the result was fused to classify the whole epithelium. This research extends the previous research by dividing each of the 10 segments into 3 parts and uses a convolutional neural network to classify the 3 parts. The result is then fused to classify the segments and the whole epithelium. The experimental data consists of 65 images. The proposed method accuracy is 77.25% compared to 75.75% using the previous method for the same dataset. (C) 2017 The Authors. Published by Elsevier B.v.

关键词： Cervical Cancer Convolutoin Neural Networks Data Fusion image classifcation Clinical Decision Support systems

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Application of superpixel segmentation and morphological projector for structural changes detection in remote sensing images

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Journal of Physics: Conference Series 2019年第3期1368卷

作者： Denisova, A Y Egorova, A A Sergeyev, v v Samara National Research University Moskovskoe Shosse 34A Samara Russia 443086 Samara National Research University Moskovskoe Shosse 34A Samara Russia 443086 Image Processing Systems Institute of RAS - Branch of the FSRC “Crystallography and Photonics” RAS Molodogvardejskaya street 151 Samara Russia 443001

Detection of structural changes in images is one of the important tasks of remote sensing (RS) data thematic analysis. The effective way to solve it is applying the Pyt'ev’s morphological projector to the pair of images of the same scene acquired on different dates. The main advantage of this method is its invariance to global brightness transformations, which in the case of RS images correspond to different parameters of the atmosphere or the different values of the brightness-contrast ratio of the scene. However, the classical Pyt'ev’s morphological projector and its regularized versions do not take into account the spatial connectivity of image samples. As a result, they ignore the textural features of images. In this article, we suggest the algorithm of structural changes detection based on superpixel segmentation and Pyt'ev’s morphological projector that takes into account local characteristics of the image pixels. In the experimental research, we analyzed the accuracies of the proposed and classical Pyt'ev’s structural change detection methods using simulated and real RS images. The comparison of two algorithms showed that the proposed method is more robust to the additive white Gaussian noise (AWGN) at different values of signal-to-noise (SNR) ratio. Additionally, the experiments with nonlinear brightness distortions (vignetting) of one of the pair of images demonstrated that the proposed method has lower false positive rates than the classical one.

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