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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Neshatpour, Katayoun Koohi, Arezou Farahmand, Farnoud Joshi, Rajiv Rafatirad, Setareh Sasan, Avesta Homayoun, Houman George Mason Univ Fairfax VA 22030 USA IBM TJ Watson Yorktown Hts NY USA

ISBN: (纸本)9781479953417

Most hospitals today are dealing with the big data problem, as they generate and store petabytes of patient records most of which in form of medical imaging, such as pathological images, CT scans and X-rays in their datacenters. Analyzing such large amounts of biomedical imaging data to enable discovery and guide physicians in personalized care is becoming an important focus of data mining and machine learning algorithms developed for biomedical Informatics (BMI). algorithms that are developed for BMI heavily rely on complex and computationally intensive machine learning and data mining methods to learn from large data. The high processing demand of big biomedical imaging data has given rise to their implementation in high-end server platforms running software ecosystems that are optimized for dealing with large amount of data including Apache Hadoop and Apache Spark. However, efficient processing of such large amount of imaging data running computational intensive learning methods is becoming a challenging problem using state-of-the-art high performance computing server architectures. To address this challenge, in this paper, we introduce a scalable and efficient hardware acceleration method using low cost commodity FPGAs that is interfaced with a server architecture through a high speed interface. In this work we present a full end-to-end implementation of big data image processing and machine learning applications in a heterogeneous CPU+FPGA architecture. We develop the MapReduce implementation of K-means and Laplacian Filtering in Hadoop Streaming environment that allows developing mapper functions in non-Java based languages suited for interfacing with FPGA-based hardware accelerating environment. We accelerate the mapper functions through hardware+software (HW+SW) co-design. We do a full implementation of the HW+SW mappers on the Zynq FPGA platform. The results show promising kernel speedup of up to 27x for large image data sets. This translate to 7.8x and 1.8

关键词： Field programmable gate arrays (FPGA)

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Distance Measuring Equipment Interference Suppression Based on Parametric Estimation and Wavelet-Packet Transformation for Global Navigation Satellite systems

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC systems 2016年第4期52卷 1607-1617页

作者： Wu, Renbiao Wang, Wenyi Li, Liuli Lu, Dan Wang, Lu Civil Aviat Univ China Tianjin Key Lab Adv Signal Proc Tianjin 300300 Peoples R China

It is well known that some global navigation satellite system (GNSS) signals operate on the aeronautical radionavigation services (ARNS) frequency band, which is also utilized by other aeronautical service signals, such as pulsed signals from the distance-measuring equipment (DME) system. Thus, the high-power DME signal, as interference, will significantly degrade the performance of the GNSS. Some algorithms, including time blanking, frequency notch filtering, and hybrid filtering, have been proposed to suppress DME interference. However, when the density of the DME pulse is high, they will bring a huge loss of the desired satellite signal. This paper proposes a hybrid approach for DME interference suppression by combining a novel parametric algorithm and the wavelet-packet-based algorithm. An overlap detection algorithm is also proposed to automatically switch between the two algorithms. When there is no overlapped pulse, the parametric method will be utilized to suppress the interference and retain more of the desired satellite signal. For overlapped DME pulses, the interferences are suppressed by the wavelet-packet transformation algorithm. The problem of parameter selection for wavelet-packet transformation is also discussed systematically. The trade-off between performance and complexity is obtained by adaptively selecting between the traditional algorithm and the proposed hybrid approach based on a pulse density detection algorithm. Numerical results are presented to demonstrate the effectiveness of the proposed approach.

关键词： Global Positioning System image edge detection Interference suppression Satellites Signal processing algorithms Time-domain analysis

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A Methodology for Hierarchical image Segmentation Evaluation 16th

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

作者： Tinguaro Rodriguez, J. Guada, Carely Gomez, Daniel Yanez, Javier Montero, Javier Univ Complutense Madrid Fac Math E-28040 Madrid Spain Univ Complutense Madrid Fac Stat E-28040 Madrid Spain

ISBN: (纸本)9783319405964;9783319405957

This paper proposes a method to evaluate hierarchical image segmentation procedures, in order to enable comparisons between different hierarchical algorithms and of these with other (non-hierarchical) segmentation techniques (as well as with edge detectors) to be made. The proposed method builds up on the edge-based segmentation evaluation approach by considering a set of reference human segmentations as a sample drawn from the population of different levels of detail that may be used in segmenting an image. Our main point is that, since a hierarchical sequence of segmentations approximates such population, those segmentations in the sequence that best capture each human segmentation level of detail should provide the basis for the evaluation of the hierarchical sequence as a whole. A small computational experiment is carried out to show the feasibility of our approach.

关键词： image segmentation Hierarchical network clustering Edge-based image segmentation evaluation

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Hyperspectral image compression for transmission over communication channel

Hyperspectral image compression for transmission over commun...

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2016 International Conference Information Technology and Nanotechnology, ITNT 2016

作者： Glumov, N.I. Gashnikov, M.V. Samara National Research University Samara Russia

In this paper, we describe a modification of the previously developed on-board image processing method applied to hyperspectral images. algorithms on which the method is based were finalized and parametrically adjusted. Computational experiments consider formation and storage specifics for hyperspectral images. It has been shown that the proposed method based on HGI-compression can be recommended for implementation in on-board processing systems and transmission over communication channels.

关键词： Digital storage

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LSB steganography with usage of Mojette Transform for secret image scrambling 23

LSB steganography with usage of Mojette Transform for secret...

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23rd International Conference on systems, Signals and image processing, IWSSIP 2016

作者： Oravec, Jakub Turán, Ján Ovseník, Luboš Department of Electronics and Multimedia Communications Faculty of Electrical Engineering and Informatics Technical University of Košice Park Komenského 13 Košice Slovakia

ISBN: (纸本)9781467395557

Many steganographic algorithms have been proposed until these days. They all try to hide information by relying on some of well-known techniques. However, each of these techniques has its advantages and also its drawbacks. In this paper, we have investigated a possibility of using tool known as Mojette Transform for modifying and scrambling a binary image containing secret information. The image after these processes should resemble noisy picture. Modified image is then embedded into the least significant bit plane of cover image. The used techniques should result in better values of parameters as MSE, or PSNR in comparison with performance of the classical Least Significant Bit steganography. © 2016 IEEE.

关键词： Binary images

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Comparative Performance Study of Various Content Based image Retrieval Methods 1

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1st International Conference on Information and Communication Technology for Intelligent systems (ICTIS)

作者： Shah, Rushabh Vaghela, Jeetendra Surve, Khyati Shah, Rutvi Sharma, Priyanka Mishra, Rasendu Patel, Ajay Datt, Rajan Nirma Univ Inst Technol Ahmadabad Gujarat India Shri Chimanbhai Patel Inst Comp Applicat Ahmadabad Gujarat India Raksha Shakti Univ Ahmadabad Gujarat India

ISBN: (数字)9783319309330

ISBN: (纸本)9783319309330;9783319309323

With the increase in the data storage and data acquisition technologies there is an increase in huge image database. Therefore we need to develop proper and accurate systems to manage this database. Here in this paper we focus on the transformation technique to search, browse and retrieve images from large database. Here we have discussed briefly about the CBIR technique for image retrieval using Discrete Cosine Transform for generating feature vector. We have researched on the different retrieval algorithms. The proposed work is experimented over 9000 images from MIRFLIKR Database (Huskies ACM International Conference on Multimedia Information Retrieval (MIR'08), 2008 [1]). We have focused on showing the difference between the precision and recall and also the time of different methods and its performance by querying an image from the database and a non-database image.

关键词： Content based image retrieval image retrieval methods image processing techniques Digital image processing

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Performance Evaluation of image Retrieval systems using Shape Feature Based on Wavelet Transform 2

Performance Evaluation of Image Retrieval Systems using Shap...

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2nd International Conference on Cognitive Computing and Information processing (CCIP)

作者： Desai, Padmashree Pujari, Jagadeesh Kinnikar, Anita BVBCET Dept CSE Hubli India SDMCET Dept ISE Dharwad Karnataka India

ISBN: (纸本)9781509010257

Digital era has produced large volume of images which created many challenges in computer science field to store, retrieve and manage images efficiently and effectively. Many techniques and algorithms have been proposed by different researcher to implement Content Based image Retrieval (CBIR) systems. This paper discusses performance of different CBIR systems implemented using combined features colour, texture and shape as a prominent feature based on wavelet transform. Choice of the feature extraction technique used in image retrieval determines performance of CBIR systems. In this paper evaluation of performance of three CBIR systems based on wavelet decomposition using threshold, wavelet decomposition using morphology operators and wavelet decomposition using Local Binary Patterns (LBP) is done. Also the performance of these methods is compared with the existing methods SIMPLIcity and FIRM. Average precision is used to compare the performance of the implemented systems. Results indicate that performance of CBIR systems using wavelet decomposition give better results than simplicity and FIRM, also wavelet decomposition with Local Binary Patterns (LBP) exhibit better retrieval efficiency compared to wavelet decomposition using threshold and morphological operators. Theses CBIR systems have been tested on bench mark Wang's image database. Precision versus Recall graphs for each system shows the performance of respective systems.

关键词： CBIR LBP Precision Recall Wavelet Decomposition

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Video segmentation in presence of static and dynamic textures 14

Video segmentation in presence of static and dynamic texture...

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image processing: algorithms and systems xiv 2016

作者： Frantc, V.A. Makov, S.V. Voronin, V.V. Marchuk, V.I. Stradanchenko, S.G. Egiazarian, K.O. Don State Technical university Dept. of Radio-Electronics Systems Gagarina 1 Rostov on Don344010 Russia Dept. of Signal Processing Tampere University of Technology Korkeakoulunkatu 1 TampereFI-33720 Finland

This paper describes an approach to video sequence over–segmentation. The objective is to split the video up to set of disjoint spatio–temporal regions with homogeneous texture properties. In the work we consider three possible types of regions: static texture, dynamic texture and non-textured region. Video over-segmentation is useful for wide range of applications, including perceptual video coding, video-based object recognition and high-level video segmentation. We treat the problem as a labeling problem on a Markov Random Field. Observed data are represented by output of fully-connected layer of convolutional neural network trained on static and dynamic textures. The hidden States of our model represent appropriate region labels. To provide robust over-segmentation we employ energy function composed of terms associated with neighboring voxels similarity and smoothness of obtained supervoxels. We show that our approach is able to segment static and dynamic textures in simultaneous fashion. We have tested our approach on several video sequences rich of static and dynamic textures and it has shown promising results. © 2016 Society for Imaging Science and Technology.

关键词： Object recognition

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A New image Clustering Method Based on the Fuzzy Harmony Search Algorithm and Fourier Transform

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JOURNAL OF INFORMATION processing systems 2016年第4期12卷 555-576页

作者： Bekkouche, Ibtissem Fizazi, Hadria Univ Sci & Technol Oran Mohamed Boudiaf Fac Math & Comp Sci Dept Comp Sci Oran Algeria

In the conventional clustering algorithms, an object could be assigned to only one group. However, this is sometimes not the case in reality, there are cases where the data do not belong to one group. As against, the fuzzy clustering takes into consideration the degree of fuzzy membership of each pixel relative to different classes. In order to overcome some shortcoming with traditional clustering methods, such as slow convergence and their sensitivity to initialization values, we have used the Harmony Search algorithm. It is based on the population metaheuristic algorithm, imitating the musical improvisation process. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. We propose in this paper a new unsupervised clustering method called the Fuzzy Harmony Search-Fourier Transform (FHS-FT). It is based on hybridization fuzzy clustering and the harmony search algorithm to increase its exploitation process and to further improve the generated solution, while the Fourier transform to increase the size of the image's data. The results show that the proposed method is able to provide viable solutions as compared to previous work.

关键词： Fourier Transform Fuzzy Clustering Harmony Search processing image Remote Sensing

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MULTI-image SUPER-RESOLUTION USING A DUAL WEIGHTING SCHEME BASED ON VORONOI TESSELLATION 23

MULTI-IMAGE SUPER-RESOLUTION USING A DUAL WEIGHTING SCHEME B...

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23rd IEEE International Conference on image processing (ICIP)

作者： Baetz, Michel Eichenseer, Andrea Kaup, Andre Friedrich Alexander Univ Erlangen Nurnberg Multimedia Commun & Signal Proc Cauerstr 7 D-91058 Erlangen Germany

ISBN: (纸本)9781467399616

Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super resolution algorithms to realize an increased resolution. Those methods can be divided into approaches that rely on only a single low resolution image or on multiple low resolution video frames. While incorporating more frames into the super-resolution is beneficial for the resolution enhancement in principle, it is also likely to introduce more artifacts from inaccurate motion estimation. To alleviate this problem, various weightings have been proposed in the literature. In this paper, we propose an extended dual weighting scheme for an interpolation-based super-resolution method based on Voronoi tessellation that relies on both a motion confidence weight and a distance weight. Compared to non-weighted super-resolution, the proposed method yields an average gain in luminance PSNR of up to 1.29 dB and 0.61 dB for upscaling factors of 2 and 4, respectively. Visual comparisons substantiate the objective results.

关键词： Resolution Enhancement image processing Multi-image Super-Resolution Voronoi Tessellation

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