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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VI"

共 15614 条记录，以下是4591-4600 订阅

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Slope-based wavefront sensor optimisation with multi-resolution analysis 6

Slope-based wavefront sensor optimisation with multi-resolut...

引用

conference on Adaptive Optics systems vi

作者： Pal, S. Clare, R. Lambert, A. Weddell, S. J. Univ Canterbury Dept Elect & Comp Engn Christchurch New Zealand UNSW Canberra Sch Engn & Informat Technol Canberra ACT Australia

ISBN: (数字)9781510619609

ISBN: (纸本)9781510619609

The predominant effect of the atmosphere on the incoming wavefront of an astronomical object is the introduction of phase distortion, resulting in an aberrated image from ground-based telescopes. Since wavefront perturbations cannot be directly measured from an image, a wavefront sensor can use intensity variations from a point source to measure specific wavefront aberrations. However, processing of measured aberration data from these sensors can be computationally intensive and this is a challenge for real-time image restoration. To accurately represent such wavefront aberrations with improved processing time, we analyse how the ridgelet transform can be used with the slope-based wavefront sensor i.e., geometric wavefront sensor, in an open-loop configuration. Ridgelet analysis is performed in the Radon domain, where each Radon line integral is computed over N angles, and is represented by a wavelet. Contrasting the behaviour of the ridgelet transform to generate Zernike polynomials with the geometric wavefront sensor, which uses the properties of geometric optics, is the main aim of this paper. We first decompose the image into a Radon domain, and then analyse each line integeral of a Radon transform by a wavelet transform. We show that multi-resolution geometric analysis with ridgelets results in lower wavefront errors, particularly for low photon counts, and computational efficiency of the geometric wavefront sensor is improved by almost a factor of 2.

关键词： wavefront sensing image restoration wavefront aberration ridgelet transform curvelet transform

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Cascaded Deep Hashing for Large-Scale image Retrieval 25th

Cascaded Deep Hashing for Large-Scale Image Retrieval

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25th International conference on Neural Information processing (ICONIP)

作者： Lu, Jun Zhang, Li Soochow Univ Sch Comp Sci & Technol & Joint Int Res Lab Machine Learning & Neuromorph Comp Suzhou 215006 Jiangsu Peoples R China Soochow Univ Prov Key Lab Comp Informat Proc Technol Suzhou 215006 Jiangsu Peoples R China

ISBN: (纸本)9783030042240;9783030042233

It is very crucial for large-scale image retrieval tasks to extract effective hash feature representations. Encouraged by the recent advances in convolutional neural networks (CNNs), this paper presents a novel cascaded deep hashing (CDH) method to generate compact hash codes for highly efficient image retrieval tasks on given large-scale datasets. Specifically, we ingeniously utilize three CNN models to learn robust image feature representations on a given dataset, which solves the issue that categories with poor feature representation have a fairly low retrieval precision. Experimental results indicate that CDH outperforms some state-of-the-art hashing algorithms on both CIFAR-10 and MNIST datasets.

关键词： image retrieval Convolutional neural networks Hash code image representation

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Methods of crypto protection of color image pixels in different code systems 8

Methods of crypto protection of color image pixels in differ...

引用

8th International conference Advanced Computer Information Technologies, ACIT 2018

作者： Vozna, Nataliia Nykolaichuk, Yaroslav Volynskyi, Orest Humennyi, Petro Sydor, Andrij Department of Specialized Computer Systems Ternopil National Economic University 8 Chekhova str Ternopil Ukraine Department of Cyber Security Ternopil National Economic University 8 Chekhova str. Ternopil Ukraine

ISBN: (纸本)9789666544899

The relevance of the development of theoretical foundations, methods and algorithms for encoding color image pixels by the problem-oriented multifunctional data structuring and the representation of color image code pixels in Rademacher (R), Krestenson (K), Rademacher-Krestenson (RK), Haar-Krestenson (HK) and Galois (G) systems is substantiated in this article. The purpose of the research is to increase the efficiency of the algorithms for digital image transforms, processing and recognition using modular arithmetic of extended Galois fields on the basis of mathematics of arithmetic operations of a non-positional residue number system. Copyright © 2018 for the individual papers by the papers'authors.

关键词： Pixels

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Near Field Active Imaging Using Sparse Arrays 52

Near Field Active Imaging Using Sparse Arrays

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52nd Asilomar conference on Signals, systems and Computers, ACSSC 2018

作者： Rajamaki, Robin Koivunen, visa Department of Signal Processing and Acoustics Aalto University Espoo02150 Finland

ISBN: (纸本)9781538692189

Sensor arrays designed for far field operation may experience performance degradation when imaging near field objects. Specifically, sparse active arrays utilizing the additional degrees of freedom provided by the sum co-array are susceptible to these effects, as the co-array depends on both the range and direction of scatterers close to the array. Consequently, a uniform far field sum co-array may become non-uniform in the near field. As a result, co-array processing algorithms, such as image addition, are subject to undesired grating lobes in the presence of near field scatterers. This paper proposes an extension to image addition for mitigating such undesired distortions. The method compensates for near field effects by computing spatially varying transmit and receive element weights. These weights minimize the discrepancy between the desired and achieved near field point spread function, while using as few image addition components as possible. Given a desired point spread function and a set of calibration measurements of the near field array steering vectors, a regularized convex optimization problem is then solved for each pixel of the image. © 2018 IEEE.

关键词： Optical transfer function

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Comparison of Semantic Classification algorithms on SAR images 26

Comparison of Semantic Classification Algorithms on SAR Imag...

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26th IEEE Signal processing and Communications Applications conference (SIU)

作者： Turkmenli, Ilter Kayabol, Koray Aptoula, Erchan Gebze Tekn Univ Elekt Muhendisligi Bolumu Gebze Turkey Gebze Tekn Univ Bilisim Teknolojileri Enstitusu Gebze Turkey

ISBN: (纸本)9781538615010

The improvements in SAR systems lead to obtain higher resolution images and consequently to increase the need for semantic classification of these images. In this paper, approximate sparse multinomial logistic regression (ASMLR) method is proposed for semantic classification of SAR images. Real SAR images are patch-based semantically classified using different feature extraction and classification methods and the classification performances are compared.

关键词： SAR image feature extraction patch based semantic classification ASMLR

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Remote sensing imagery segmentation based on multi-objective optimization algorithms

Remote sensing imagery segmentation based on multi-objective...

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5th IEEE Latin American conference on Computational Intelligence (LA-CCI)

作者： Hinojosa, Salvador Avalos, Omar Galvez, Jorge Oliva, Diego Cuevas, Erik Perez-Cisneros, Marco Univ Complutense Madrid Fac Informat Dept Ingn Software & Inteligencia Artificial Madrid Spain Univ Guadalajara CUCEI Div Elect & Computac Guadalajara Jalisco Mexico

ISBN: (纸本)9781538646267

Remote Sensing (RS) has been used to obtain relevant information about objects without the explicit necessity to stay in contact with them. RS collects measured data from the emanated energy of the surface of the earth. This process aims the construction of knowledge-based systems to identify interesting geographic features automatically. In RS, multispectral image segmentation is one of the most widespread methodologies for information extraction, using schemes comprising a wide variety of hard and soft grouping mechanisms based on different non-standard similarity measures making the classification problem to be application dependent. This procedure uses the spectral information contained in an image to recognize regions of interest. The segmentation of multispectral images is usually conducted by performing segmentation over a specific band according to the application. However, the segmentation of a specific channel might not perform well on the other bands of the image. This paper proposes a general scheme for multispectral imagery segmentation using multi-objective evolutionary algorithms (MOEAs) to identify thresholds encoding the best trade-offs between the segmentation criteria of various channels of the multispectral image. An evaluation of the performance of the proposed methodology is presented over a multispectral benchmark set composed of different images complexities and compared with several multi-objective algorithms.

关键词： evolutionary algorithms multi-objective optimization image processing thresholding remote sensing

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A Novel Calibration Algorithm for Timing Mismatch in Time-Interleaved ADCs

A Novel Calibration Algorithm for Timing Mismatch in Time-In...

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International conference on Frontiers of Signal processing (ICFSP)

作者： Yu Cao Peng Miao Fei Li School of Southeast Nanjing China

Timing skews often generate undesirable spurs in time-interleaved ADCs (TIADC) and degrade the systems' performance seriously. In this paper, an efficient background timing skew calibration algorithm is proposed to minimize its effects. The proposed Algorithm detects the sampling-time mismatches between sub-ADCs by estimating the skew-related errors with a reference channel and aligns the sampling edge of each sub-ADC to that of the reference channel by analog variable-delay lines in the negative feedback loop. Compared with conventional background calibration methods based on complex algorithms or serious input restrictions, the proposed technique detects timing skews by only negligible hardware consisting of simple digital blocks and is applicable for a wide range of input including completely random signals. The detailed theoretical analysis and sufficient simulated results revealed that this calibration algorithm can greatly attenuate skew-related spurs and improve the property of the TIADC system significantly. What's more, it's not sensitive to some non-ideal components in actual circuits like mismatches between channels or jitters in clock circuits, which verifies the practicability and robustness of this method.

关键词： Calibration Timing image edge detection Clocks Signal processing algorithms Delay lines Bandwidth

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A Framework for Background Modeling Using Vehicle-to-Infrastructure Communication for Improved Candidate Generation in Pedestrian Detection

A Framework for Background Modeling Using Vehicle-to-Infrast...

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IEEE International conference on Electro/Information Technology (EIT)

作者： Al-refai, Ghaith Horani, Modar Rawashdeh, Osamah A. Oakland Univ Dept Elect & Comp Engn Rochester MI 48063 USA

ISBN: (纸本)9781538653982

vision-based pedestrian detection is an essential part of Advanced Driver Assistance systems (ADAS). A pedestrian detection system involves several processing steps including image acquisition, candidate generation, classification, and real-time tracking. Typical approaches for pedestrian candidate generation scan the whole image, which is time consuming. Intelligent generation of potential pedestrian candidates, by reducing the number of the unnecessary candidates, may improve the detection accuracy and reduce the runtime of detection algorithms. This paper introduces a new framework for improved candidate generation using background modeling. The proposed method leverages Vehicle-to-Infrastructure (V21) communication for sharing of image frames. The system architecture is introduced and defined in-terms of requirements and tasks. Promising initial results for background modeling and moving object detection are provided with discussion and suggestions for future work.

关键词： Cameras Roads Global Positioning System Databases image edge detection Feature extraction Real-time systems

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Modeling Complex Building Structure (LoD2) Using image-Based Point Cloud 3

Modeling Complex Building Structure (LoD2) Using Image-Based...

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3rd IEEE International conference on image processing, Applications and systems (IPAS)

作者： Ahmed, Wael Shi, Wenzhong Xu, Wenbin Hong Kong Polytech Univ Land Surveying & Geoinformat Kowloon Hong Kong Peoples R China

ISBN: (纸本)9781728102474

A method designed to reconstruct outdoor 3D building models automatically from a point cloud is presented in this paper. The proposed approach starts with building detection using spectral and spatial data from the UAV point cloud to remove non-building features. RANSAC, modified convex hull, and line growing algorithms are used to extract main roof planes and their boundaries. Roof planes are adjusted to each other using geometrical constraints, the height of each plane is estimated and a 3D model for the whole structure is constructed with LoD2. The key contribution of this approach is using a hybrid approach of model-driven with statistical analysis for modeling complex structures from a noisy point cloud. The reconstructed model shows that the workflow is sufficient to describe the whole building structure in the required LoD.

关键词： UAV RANSAC Model Driven LoD2 Outdoor Modeling

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Automatic segmentation of lung cancer cells with the new parameters by using methods of image processing and analysis.

Automatic segmentation of lung cancer cells with the new par...

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Innovations in Biomedical Engineering (IBE) conference

作者： Jedrusik, Przemyslaw Koprowski, Robert Bednarek, Ilona Wrobel, Zygmunt Univ Silesia Dept Comp Biomed Syst Inst Comp Sci Ul Bedzinska 39 PL-41200 Sosnowiec Poland Med Univ Silesia Dept Biotechnol & Genet Engn Sch Pharm Div Lab Med Sosnowiec Ul JednoAZci 8 PL-41200 Sosnowiec Poland

ISBN: (纸本)9783319700632;9783319700625

Modern diagnostic methods allow to get multiple information regarding research material. This work focused on the development of an algorithm for automatically determining the correct number of cells. The developed tool allows the detection of cells as individual objects, searching for the objects significantly larger than the sought and checking if they were a combination of objects. The algorithm was based on additional parameters designated in its subsequent steps as well as their respective correcting claimed searched result. Analyzed a large number of images, it was found that there is a close relationship between the surface area of the cells, the degree of extension and the location and correct detection of objects that are neither a cluster of cells, and nothing significant image artifacts. The developed algorithm was written using Matlab software.

关键词： image processing algorithms automatic lung cancer cell culture cell migration

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