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Conference on applications of Digital image processing XXXviii

作者： Dufaux, Frederic Xing, Yafei Pesquet-Popescu, Beatrice Schelkens, Peter Telecom ParisTech Inst Mines Telecom CNRS LTCI F-75013 Paris France Vrije Univ Brussel Dept Elect & Informat ETRO B-1050 Brussels Belgium IMinds Dept Future Media & Imaging B-9050 Ghent Belgium

ISBN: (纸本)9781628417654

Holography has the potential to become the ultimate 3D experience. Nevertheless, in order to achieve practical working systems, major scientific and technological challenges have to be tackled. In particular, as digital holographic data represents a huge amount of information, the development of efficient compression techniques is a key component. This problem has gained significant attention by the research community during the last 10 years. Given that holograms have very different signal properties when compared to natural images and video sequences, existing compression techniques (e.g. JPEG or MPEG) remain suboptimal, calling for innovative compression solutions. In this paper, we will review and analyze past and on-going work for the compression of digital holographic data.

关键词： Digital holography computer generated holography wavelets direction-adaptive discrete wavelet transform packet decompositions vector lifting scheme JPEG 2000 image compression

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2015 23rd signal processing and Communications applications Conference, SIU 2015 - Proceedings

2015 23rd Signal Processing and Communications Applications ...

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2015 23rd signal processing and Communications applications Conference, SIU 2015

ISBN: (纸本)9781467373869

The proceedings contain 651 papers and 1 PowerPoint presentation. The topics discussed include: optical disc detection based on intensity and feature in the retinal images;classification with extreme learning machine and ensemble algorithms over randomly partitioned data;cryptography with compressive sensing orthogonal matching pursuit method;detecting the attention state of an operator in continuous attention task using EEG-based brain-computer interface;ensemble methods for opinion mining;cooperative spectrum sharing for cognitive radio networks using spatial modulation at secondary users;analysis of negativity and relative entropy of entanglement measures for qubit-qutrit quantum communication systems;a novel approach for image compression based on multi-level image thresholding using discrete wavelet transform and cricket algorithm;modelling black hole attacks on cluster-based wireless sensor networks;and improving the LEACH protocol on wireless sensor network.

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MULTI-RESOLUTION SUPER-PIXELS AND THEIR applications ON FLUORESCENT MESENCHYMAL STEM CELLS imageS USING 1-D SIFT MERGING

MULTI-RESOLUTION SUPER-PIXELS AND THEIR APPLICATIONS ON FLUO...

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IEEE International Conference on image processing (ICIP)

作者： Yorulmaz, Onur Oguz, Oguzhan Akhan, Ece Tuncel, Donus Atalay, Rengul C. Cetin, A. Enis Bilkent Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey Bilkent Univ Dept Chem TR-06800 Ankara Turkey Bilkent Univ Dept Mol Biol & Genet TR-06800 Ankara Turkey Middle E Tech Univ Dept Informat TR-06800 Ankara Turkey

ISBN: (纸本)9781479983391

A new multi-resolution super-pixel based algorithm is proposed to track cell size, count and motion in Mesenchymal Stem Cells (MSCs) images. Multi-resolution super-pixels are obtained by placing varying density seeds on the image. The density of the seeds are determined according to the local high frequency components of the MSCs image. In this way a multi-resolution super-pixels decomposition of the image is obtained. A second contribution of the paper is novel decision rule for merging similar neighboring super-pixels. One-dimensional version of the well known scale invariant feature transform (SIFT) is developed and applied to the histograms of the neighboring super-pixels to determine similar regions. The proposed algorithm is experimentally shown to be successful in segmenting and tracking cells in MSCs images.

关键词： Stem cell tracking multi-resolution super-pixels wavelet SIFT decomposition fluorescent image

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Hierarchical Lossless image Compression for Telemedicine applications 11

Hierarchical Lossless Image Compression for Telemedicine App...

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11th International Conference on image and signal processing (ICISP)

作者： Sumalatha, R. Subramanyam, M. V. Santhiram Engn Coll Nandyal India G Pullaiah Coll Engn & Technol Kurnool 518002 India

The main aim of hierarchical lossless image compression is to improve accuracy, reduce the bit rate and improve the compression efficiency for the storage and transmission of the medical images while maintain an acceptable image quality for diagnosis purpose. The cost and limitation in bandwidth of wireless channels has made compression is necessity in today's era. In medical images, the contextual region is an area which contains an important information and must be transmitted without distortion. In this paper the selected region of the image is encoded with Adaptive Multiwavelet Transform AMWT) using Multi Dimensional Layered Zero Coding (MLZC). Experimental results shows that Peak signal to Noise Ratio (PSNR), Correlation Coefficient (CC), Mean Structural Similarity Index (MSSIM) performance is high and Root Mean Square Error (RMSE), Mean Absolute Error (MAE) values are low, and moderate Compression Ratio (CR) at high Bits Per Pixel (BPP) when compared to the integer wavelet and multiwavelet transform. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/). Peer-review under responsibility of Universal Society for Applied Research

关键词： AMWT Contextual region Hierarchical image coding MLZC Multiwavelet

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A Selective Bitplane Based Encryption of Grayscale images with Tamper Detection, Localization and Recovery Based on Watermark 2

A Selective Bitplane Based Encryption of Grayscale Images wi...

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2nd International Conference on Information Systems Design and Intelligent applications (INDIA)

作者： Som, Sukalyan Sen, Sayani Mahapatra, Suman Palit, Sarbani Barrackpore Rastraguru Surendranath Coll Dept Comp Sci Kolkata India Univ Kalyani Dept Comp Sci & Engn Kalyani 741235 W Bengal India Indian Stat Inst CVPR Unit Kolkata India

ISBN: (纸本)9788132222507;9788132222491

Ciphered data need an additional level of protection in order to safeguard them from being tampered after the decryption phase. Ciphered data, upon being deciphered by the intended receiver, is unprotected and it can be easily doctored by ever-developing, sophisticated image processing softwares. In the proposed scheme, we introduce a selective bitplane based encryption of grayscale images coupled with the facility of tamper detection, localization and restoration based on DWT based digital watermark. The original image is first sub-divided into blocks where Discrete wavelet Transform (DWT) is applied to generate the watermark. This is embedded in four disjoint portions of the image to increase the probability of restoration of the tampered image from tampers. To add another level of security to the transmission of the watermarked image a selective bitplane based encryption based on chaos is applied. The watermarked image is first partitioned into its constituent bitplanes and then first four bitplanes from Most Significant Bitplane (MSB) is encrypted by a chaos based pseudorandom binary number generator (PRBG). The enciphered bitplanes are concatenated with unencrypted ones to produce the cipher watermarked image. The validity and novelty of the proposed scheme is verified through exhaustive simulations using different images of two well-known image databases.

关键词： Discrete wavelet transform Chaos Cryptography 1D logistic map Information entropy Peak-signal-to-noise-ratio (PSNR)

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An adaptive projection algorithm for multirate filter bank optimization 8

An adaptive projection algorithm for multirate filter bank o...

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8th European signal processing Conference, EUSIPCO 1996

作者： Huang, Dong-Yan Regalia, Phillip A. Departement Signal and Image Institut National des Telecommunications 9 rue Charles Fourier Evry cedexF-91011 France

We develop a new algorithm for multirate filter bank optimization, which finds application in subband coding or wavelet signal analysis. Although some impressive off-line algorithms have recently been developed for this purpose, the computation demand of such algorithms often renders them prohibitive for real-time applications. In this vein, adaptive filtering solutions remain of interest. A simple gradient descent algorithm may be ill suited due to the nonquadratic nature of the cost function to be minimized, and accordingly non gradient algorithms may offer some attractive alternatives. The present paper describes a projection type algorithm, which aims to construct a lossless filter bank such that one of its impulse responses lies close to an extremal eigenvector of the input signal autocorrelation matrix. Though a formal convergence proof of the algorithm is not offered, simulations show that the algorithm converges to an acceptable vicinity of the global minimum point of the cost function. © 2015 European signal processing Conference, EUSIPCO. All rights reserved.

关键词： Cost functions

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农业物联网数字图像传输中小波分析的应用

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中国农业文摘（农业工程） 2016年第5期28卷 18-21页

作者：曾辉易大国卓辉方逵湖南农业大学信息科学技术学院湖南长沙410128 湖南生物机电职业技术学院湖南长沙410128

本文通过对小波变换—信号滤波国内外研究现状、引入传统Fourier分析和开窗Fourier变换在图像处理上不足,提出针对图像整体时频域和局部时频域——小波变换算法;接着介绍小波分析在农业物联网数字图像处理上传输应用可行性(如图像处理... 详细信息

本文通过对小波变换—信号滤波国内外研究现状、引入传统Fourier分析和开窗Fourier变换在图像处理上不足,提出针对图像整体时频域和局部时频域——小波变换算法;接着介绍小波分析在农业物联网数字图像处理上传输应用可行性(如图像处理精准度高、占用频带较宽,数据压缩能力强、图像再现效果好、灵活度高、适用面广)等特点。这将对农业物联网数字图像信号处理之后,能够依然保持相邻尺度间具有很强的关联性,因而方便对农业物联网中农作物生长、农产品加工与流通方面图像特征提取和保持原有信号不变。

关键词：小波变换数字图像滤波农业物联网

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A wireless video multicasting scheme based on multi-scale compressed sensing

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EURASIP JOURNAL ON ADVANCES IN signal processing 2015年第1期2015卷 1-11页

作者： Wang, Anhong Wu, Qingdian Ma, Xiaoli Zeng, Bing Taiyuan Univ Sci & Technol Inst Digital Media & Commun Taiyuan Shanxi Peoples R China Georgia Inst Technol Atlanta GA 30332 USA Univ Elect Sci & Technol China Inst Image Proc Chengdu 610054 Sichuan Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Kowloon Hong Kong Peoples R China

Video multicast is becoming more and more popular in wireless multimedia applications, in which one major challenge is to offer heterogeneous users with a graceful degradation against varying packet loss ratios and channel noise. In this paper, we propose a multi-scale compressed sensing-based wireless video multicast scheme, abbreviated as MCS-cast. The encoder of MCS-cast decomposes each video frame through a discrete wavelet transform (DWT) and explores an optimized compressed sensing (CS) rate to sample/measure each DWT level. The CS measurements are then packed in such a way that all packets are made as equally important as possible, while each packet includes different percentages of different DWT levels. Finally, the packets are transmitted via an analog-like modulator with mapping of the measurements into a very dense constellation. We demonstrate that because of larger percentages of more important DWT levels in each packet, packet loss leads to a much reduced influence on the reconstruction quality. Experimental results show that our MCS-cast preserves the property of graceful degradation for heterogeneous users and can outperform the state-of-the-art SoftCast by up to 3 dB in PSNR at high packet loss ratios (over the same noisy channel).

关键词： Multi-scale Compressed sensing Video multicast Discrete wavelet transform

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Using image processing on MRI Scans

Using Image Processing on MRI Scans

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2015 IEEE International Conference on signal processing, Informatics, Communication and Energy Systems, SPICES 2015

作者： Patil, Chetan Mathura, M.G. Madhumitha, S. David, S. Sumam Fernandes, Merwyn Venugopal, Anand Unnikrishnan, B. Dept. of EandC NITK Surathkal Mangalore575025 India Dept. of Radiology Kasturba Medical College Mangalore575001 India Dept. of Community Medicine Kasturba Medical College Mangalore575001 India

ISBN: (纸本)9781479918232

Alzheimer's disease (AD) is an irreversible and progressive brain disease that gradually destroys memory and thinking skills to an extent that it starts affecting the daily life. It has become the most common cause of dementia among older people. The work presented in this paper evaluates the utility of image processing on the Magnetic Resonance Imaging (MRI) scans to estimate the possibility of an early detection of AD. The total brain atrophy and specifically the hippocampal atrophy are considered strong diagnostic tests for AD. T1 weighted MRIs have been used for the purpose of image processing to evaluate atrophy. The paper demonstrates the applications of several image processing techniques such as K-means clustering, wavelet transform, watershed algorithm and also a customized algorithm tailored for the specific case. It has been implemented on the open source platforms, OpenCV and Qt, which facilitates the implementation and utility of the developed product in the hospitals without requiring any proprietary software. The results obtained from the project could aid the analysis to detect AD along with correlation with the psychiatric results and could thus assist the doctors in detecting AD at an early stage. This could progressively help in understanding and treating AD. © 2015 IEEE.

关键词： image segmentation

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Classification of Basic Human Emotions from Electroencephalography Data 20th

Classification of Basic Human Emotions from Electroencephalo...

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20th Iberoamerican Congress on Pattern Recognition (CIARP)

作者： Fernandez, Ximena Garcia, Rosana Ferreira, Enrique Menendez, Juan Univ Catolica Uruguay Av 8 Octubre 2738 Montevideo 11600 Uruguay Sentia Labs Montevideo 11100 Uruguay

ISBN: (纸本)9783319257518;9783319257501

This paper explores the combination of known signal processing techniques to analyze electroencephalography (EEG) data for the classification of a set of basic human emotions. An Emotiv EPOC headset with 16 electrodes was used to measure EEG data from a population of 24 subjects who were presented an audiovisual stimuli designed to evoke 4 emotions (rage, fear, fun and neutral). Raw data was preprocessed to eliminate noise, interference and physiologic artifacts. Discrete wavelet Transform (DWT) was used to extract its main characteristics and define relevant features. Classification was performed using different algorithms and results compared. The best results were obtained when using meta-learning techniques with classification errors at 5 %. Final conclusions and future work are discussed.

关键词： Electroencephalography Discrete wavelet Transform Human emotion classification

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