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

共 13627 条记录，以下是4661-4670 订阅

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Learned D-AMP: principled neural network based compressive image recovery 17

Learned D-AMP: principled neural network based compressive i...

引用

Proceedings of the 31st International conference on Neural Information processing systems

作者： Christopher A. Metzler Ali Mousavi Richard G. Baraniuk Rice University

ISBN: (纸本)9781510860964

Compressive image recovery is a challenging problem that requires fast and accurate algorithms. Recently, neural networks have been applied to this problem with promising results. By exploiting massively parallel GPU processing architectures and oodles of training data, they can run orders of magnitude faster than existing techniques. However, these methods are largely unprincipled black boxes that are difficult to train and often-times specific to a single measurement *** was recently demonstrated that iterative sparse-signal-recovery algorithms can be "unrolled" to form interpretable deep networks. Taking inspiration from this work, we develop a novel neural network architecture that mimics the behavior of the denoising-based approximate message passing (D-AMP) algorithm. We call this new network Learned D-AMP (LDAMP).The LDAMP network is easy to train, can be applied to a variety of different measurement matrices, and comes with a state-evolution heuristic that accurately predicts its performance. Most importantly, it outperforms the state-of-the-art BM3D-AMP and NLR-CS algorithms in terms of both accuracy and run time. At high resolutions, and when used with sensing matrices that have fast implementations, LDAMP runs over 50 x faster than BM3D-AMP and hundreds of times faster than NLR-CS.

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Simulating biogeo-optical dynamics in the bottom boundary layer: Northern Gulf of Mexico test case 9

Simulating biogeo-optical dynamics in the bottom boundary la...

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conference on Ocean Sensing and Monitoring IX

作者： Jollif, Jason K. Ladner, Sherwin Smith, Travis Penko, Allison Jarosz, Ewa Lovitt, Todd Naval Res Lab Stennis Space Ctr MS 39529 USA Vencore 11091 Sunset Hills Rd Reston VA 20190 USA

ISBN: (纸本)9781510608733;9781510608740

Interdisciplinary coastal observations over a two-week period in the northern Gulf of Mexico reveal a complex and dynamic bottom boundary layer (BBL) that is characterized by both biological and suspended sediment (biogeo-) optical signals. Much of the BBL optical variance is concealed from remote sensing by the opacity of the nearly omnipresent surface river plume, however, the BBL physical dynamics and resulting optical excitation are indeed responding to surface wind stress forcing and surface gravity wave-induced turbulence. Here we present a series of numerical modeling efforts and approaches aimed towards resolving and simulating these observed biogeo- physical and -optical processes. First, we examine results from the Tactical Ocean Data System (TODS), which combines daily satellite imagery with numerical circulation model results to render a three-dimensional estimate of the optical field and then execute a reduced-order complexity advection-diffusion-reaction model to render hourly forecasts. Whereas the TODS system has the advantage of effectively assimilating both glider data and satellite images, the 3D generation algorithms still have difficulty in the northern Gulf's complex 3-layered system (surface plume, geostrophic interior, BBL). Second, we present results from the Coupled Ocean-Atmosphere Prediction (COAMPS) system that has been modified to include interactive surface-gravity wave simulations. Results from this complex numerical modeling system suggest that Stokes drift current (SDC) has a potentially major role in determining the physical and kinematic characteristics of the BBL, and will substantially impact model-based estimates of sediment resuspension and transport.

关键词： Ocean optics 3D modeling Coastal modeling Data modeling 3D image processing Complex systems Earth observing sensors Numerical modeling Satellite imaging Satellites Biomedical optics Remote sensing

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Research on the Novel Pattern Clustering Algorithm based on Particle Swarm Optimized Adaptive Wavelet Neural Network Model

Research on the Novel Pattern Clustering Algorithm based on ...

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International conference on Communication and Electronics systems (ICCES)

作者： Zheng, Zhaoxi Wu, Zeling Yu, Miao Sun Yat Sen Univ Kaohsiung Taiwan East China Univ Sci & Technol Shanghai Peoples R China Lubeck Univ Appl Sci Lubeck Germany Shandong Univ Jinan Peoples R China

ISBN: (纸本)9781509010660

image segmentation is an integral part of critical image processing applications. Segmentation involves removal of a region of interest from the background. Recent researches in segmentation incorporate clustering algorithms for separation or removal of regions of interest. Prominent segmentation algorithms include K - means which segment the region from the background and further median filtering could be utilized to remove the unwanted regions in the segmented image. This research paper utilizes an adaptive wavelet neural network model with training or learning process optimized by the particle swarm optimization algorithm. The proposed algorithm has been tested and experimental results indicate a high precision of segmentation when compared with the conventional techniques.

关键词： image segmentation neural network particle swarm optimization wavelet approximation

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A New Reweight Scheme for Bilateral and Non-local Means Approach for image Denoising 2

A New Reweight Scheme for Bilateral and Non-local Means Appr...

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2nd International conference on Communication Control and Intelligent systems (CCIS)

作者： Saraf, Ankita Punjabi Univ Dept Comp Sci Patiala Punjab India

ISBN: (纸本)9781509032105

Additive noise removal from a given image is an important task in digital image processing for which denoising algorithms are used. The goal of any denoising algorithm is to attenuate the noise properly and to preserve the useful content of an image. Although various denoising algorithms have been proposed to remove noise but there is still scope of improvement. The main focus of this paper is, first, analyze the basic denoising approaches and to compare them, second, to study post-stage filtering technique using method noise and reweight schemes. In this case study, we observe through our experiments that the post-filtering techniques have more potential to attenuate the noise properly, which is left by the initially applied denoising approach. The denoising performance of all considered methods is compared using two parameters: PSNR and MSSIM.

关键词： Bilateral Filtering Non-local Means Filtering Method Noise

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image Reconstruction by the Patch Based Inpainting 16th

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16th International conference on Information processing and Management of Uncertainty in Knowledge-based systems (IPMU)

作者： Vlasanek, Pavel Perfilieva, Irina Univ Ostrava Inst Res & Applicat Fuzzy Modeling Ostrava Czech Republic

ISBN: (纸本)9783319405964;9783319405957

The paper is focused on demonstration of image inpainting technique using the F-transform theory. Side by side with many algorithms for the image reconstruction we developed a new method of patch-based filling of an unknown (damaged) image area. The unknown area is proposed to be recursively filled by those known patches that have non-empty overlaps with the unknown area and are the closest ones among others from a database. We propose to use the closeness measure on the basis of the F-1-transform.

关键词： image processing F-transform Inpainting

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Linear in the parameter model for Homomorphic filter: Volterra series based approach 11

Linear in the parameter model for Homomorphic filter: Volter...

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11th International conference on Industrial and Information systems (ICIIS)

作者： Venkatappareddy, P. Lall, Brejesh Indian Inst Technol Dept Elect Engn New Delhi 110016 India

ISBN: (纸本)9781509038183

This paper introduces a linear in the parameter model for Homomorphic filter using Volterra series approach. To obtain these parameters we propose a model where we choose a sub image from the response of Homomorphic filter as reference image to reduce computational complexity. We apply non uniform illuminated images to the proposed filter and compare its performance against standard Homomorphic filter. The proposed filter outperforms the traditional Homomorphic filter in all experiments. Also we compare the error convergence and steady-state error of Sparse aware LMS with LMS algorithm to calculate proposed filter coefficients.

关键词： Lighting Computational modeling Convergence image processing Mathematical model Kernel Signal processing algorithms

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High speed Vedic Multiplier for image processing using FPGA 10

High speed Vedic Multiplier for Image processing using FPGA

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10th International conference on Intelligent systems and Control (ISCO)

作者： Jayakumar, S. Sumathi, S. Adhiyamaan Coll Engn Dept EIE Hosur India Adhiyamaan Coll Engn Dept ECE Hosur India

ISBN: (纸本)9781467378079

Vedic multiplier is based on the ancient algorithms (sutras) followed in INDIA for multiplication. This work is based on one of the sutras called "Nikhilam Sutra". This sutra is meant for faster mental calculation. Though faster when implemented in hardware, it consumes more power than the conventional ones. This paper presents a technique to modify the architecture of the Vedic multiplier by using some existing methods in order to reduce power and improve image processing applicatio. The 32 X 32 Vedic multiplier is coded in Verilog HDL and Synthesized using Synopsys Design Compiler. The performance is compared in terms of area, data arrival time and power with earlier existing architecture of Vedic multiplier. Filtering involves lots of multiplications which consumes time. Time required increases with the increase in the number of pixels. This paper proposes an approach for image filtering using Vedic Mathematic which performs faster multiplication compared to the conventional algorithms namely Booth and Array Multiplication Algorithm thus reducing the time required for filtering of images. Time required by the algorithms for filtering are then compared using the experimental results.

关键词： image filtering Nikhilam sutra Vedic multiplier

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Computer Vision System for Defects Detection in PET Preform 21

Computer Vision System for Defects Detection in PET Preform

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21st International conference on Methods and Models in Automation and Robotics (MMAR)

作者： Laucka, Andrius Andriukaitis, Darius Valinevicius, Algimantas Navikas, Dangirutis Kaunas Univ Technol Dept Elect Engn LT-51368 Kaunas Lithuania

ISBN: (纸本)9781509018666

The computer vision systems are mainly devoted for production monitoring in quality inspection systems. It is the fastest growing and most popular non-invasive product defects detection method. The productivity of electronic components growth and their prices decline creates favorable conditions for the development of image processing systems for industrial production. The food industry is one of the main industries. Production volumes grow along with human population growth. Containers for food industry are made in very large quantities and demand on quality inspection system plays important role. An automated computer vision system was developed for the control of PET preparation quality. The implementation of the designed system was presented in this article. The system used for image processing algorithms to inspect the lateral and upper parts of the workpiece. The system is designed according to its operating parameters. Reached throughput is 10,000 workpieces per hour.

关键词： PET computer vision systems digital image processing electronic systems

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Automatic Thresholding Method for Edge Detection algorithms 8

Automatic Thresholding Method for Edge Detection Algorithms

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8th International conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Anghelescu, Petre Iliescu, Vlad Gabriel Mara, Constantin Gavriloaia, Mihai-Bogdan Univ Pitesti Dept Elect Commun & Comp Pitesti Romania Univ Politehn Bucuresti Telecommun Dpt Elect Bucharest Romania

ISBN: (纸本)9781509020478

This paper describes an efficient edge detection algorithm that can be used as a plug-in for digital image processing systems. The proposed algorithm uses a method based on iterative clustering targeting a reduced number of operations. The algorithm splits the image into two parts, background and foreground, and calculates the mean value for each of them. Based on these results, the new threshold value will be obtained and looped until the mean values remain unchanged. The only pixels affected by the change are the pixels with values between the previous two thresholds, so only they have to be redistributed to a new class. As a result, only few operations are needed in order to obtain the desired threshold. All the algorithms and results obtained in this paper are developed and tested using the C# programming language.

关键词： image processing edge detection thresholding algorithms non-maximum suppression cluster based methods

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Spatiotemporal hazard mapping of a flood event "migration" in a Transboundary River Basin as an operational tool in Flood Risk Management

Spatiotemporal hazard mapping of a flood event "migration" i...

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conference on Active and Passive Microwave Remote Sensing for Environmental Monitoring

作者： Perrou, Theodora Papastergios, Asterios Parcharidis, Issaak Chini, Marco Harokopio Univ Athens Dept Geog Athens 17671 Greece LIST 41 Rue Brill L-4422 Luxembourg Luxembourg

ISBN: (数字)9781510613171

ISBN: (纸本)9781510613171;9781510613164

Flood disaster is one of the heaviest disasters in the world. It is necessary to monitor and evaluate the flood disaster in order to mitigate the consequences. As floods do not recognize borders, transboundary flood risk management is imperative in shared river basins. Disaster management is highly dependent on early information and requires data from the whole river basin. Based on the hypothesis that the flood events over the same area with same magnitude have almost identical evolution, it is crucial to develop a repository database of historical flood events. This tool, in the case of extended transboundary river basins, could constitute an operational warning system for the downstream area. The utility of SAR images for flood mapping, was demonstrated by previous studies but the SAR systems in orbit were not characterized by high operational capacity. Copernicus system will fill this gap in operational service for risk management, especially during emergency phase. The operational capabilities have been significantly improved by newly available satellite constellation, such as the Sentinel-1A&B mission, which is able to provide systematic acquisitions with a very high temporal resolution in a wide swath coverage. The present study deals with the monitoring of a transboundary flood event in Evros basin. The objective of the study is to create the "migration story" of the flooded areas on the basis of the evolution in time for the event occurred from October 2014 till May 2015. Flood hazard maps will be created, using SAR-based semi-automatic algorithms and then through the synthesis of the related maps in a GIS-system, a spatiotemporal thematic map of the event will be produced. The thematic map combined with TanDEM-X DEM, 12m/pixel spatial resolution, will define the non-affected areas which is a very useful information for the emergency planning and emergency response phases. The Sentinels meet the main requirements to be an effective and suitable operational

关键词： Sentinel-1 SAR image processing Transboundary river basin Flood mapping TanDEM-X DEM Flood risk management Evros River

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