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3rd International conference on Advanced Informatics for Computing Research (ICAICR)

作者： Soni, Ekta Mahajan, Rashima GD Goenka Univ Gurgaon India Manav Rachna Int Inst Res & Studies Faridabad India

ISBN: (纸本)9789811501081;9789811501074

An exponential rise in amount of medical image data generation has been recorded since two decades. In telemedicine based applications, this enormous amount of data is initially stored and later, transmitted to medical experts for required diagnosis. This whole storage and transmission process may require extremely high memory space and large transmission bandwidth. An attempt has been made to compress MRI (magnetic resonance imaging) data by exploiting neighbouring pixel redundancy found in images along with the relevant diagnostic information. A detailed analysis of MRI image compression using asymmetric wavelet based frequency transformation techniques has been carried out in MATLAB. It implements discrete wavelet transform using asymmetric mother wavelet daubechies (db) in conjunction with a hierarchal embedded bit coding scheme, set partitioning in hierarchal trees. Distinct daubechies (db6, db12, db16 and db20) mother wavelets have been applied to a set of ten MRI image (512 x 512) dataset. The performance of applied compression scheme has been evaluated by analyzing Compression-Ratio achieved, Peak-signal-to-Noise-Ratio and Bits-Per-Pixel. A high compression ratio (CR 3.84) with considerably high peak signal to noise ratio (PSNR - 43.35) is achieved with db20 wavelet. This high value of PSNR may help in preserving the diagnostic details in input MRI image data to a great extent and high CR would lead to less storage space followed by small transmission bandwidth requirement as compared to earlier compression techniques. It could definitely lead to development of more efficient remote healthcare systems.

关键词： Asymmetric wavelets Compression Compression-Ratio image MRI Peak-signal-to-Noise-Ratio wavelets

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FPGA-Based Acceleration of Expectation Maximization Algorithm using High-Level Synthesis 13

FPGA-Based Acceleration of Expectation Maximization Algorith...

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conference on Design and Architectures for signal and image processing (DASIP)

作者： Momen, Mohammad Abdul Khalid, Mohammed A. S. Oninda, Mohammad Abdul Moin Adv Micro Devices Inc 1 Commerce Valley Dr East Markham ON L3T 7X6 Canada Univ Windsor Dept Elect & Comp Engn 401 Sunset Ave Windsor ON N9B 3P4 Canada

ISBN: (纸本)9781728140742

Expectation Maximization (EM) is a soft clustering algorithm which partitions data iteratively into M clusters. It is one of the most popular data mining algorithms that uses Gaussian Mixture Models (GMM) for probability density modeling and is widely used in applications such as signal processing and Machine Learning (ML). EM requires high computation time when dealing with large data sets. This paper presents an optimized implementation of EM algorithm on Stratix V and Arria 10 FPGAs using Intel FPGA Software Development Kit (SDK) for Open Computing Language (OpenCL). Comparison of performance and power consumption between Central processing Unit (CPU), Graphics processing Unit (GPU) and FPGA is presented for various dimension and cluster sizes. Compared to Intel (R) xeon (R) CPU E5-2637, our fully optimized OpenCL model for EM targeting Arria 10 FPGA achieved up to 1000x speedup in terms of throughput (T) and 5395x speedup in terms of throughput per unit of power consumed (T/P). Compared to previous research on EM-GMM implementation on GPUs, Arria 10 FPGA obtained up to 64.74x speedup (T) and 486.78x speedup (T/P).

关键词： Expectation Maximization (EM) Gaussian Mixture Model (GMM) High-Level Synthesis (HLS) Hardware Acceleration FPGA Data Mining

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Digital signal processing for Visible Light Communication applications

Digital Signal Processing for Visible Light Communication Ap...

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Asia Communications and Photonics conference (ACP)

作者： Chow, Chi-Wai Chen, Guan-Hong Peng, Ching-Wei Wei, Liang-Yu Yeh, Chien-Hung Liu, Yang Natl Chiao Tung Univ Dept Photon Hsinchu 30010 Taiwan Natl Chiao Tung Univ Inst Electroopt Engn Hsinchu 30010 Taiwan Feng Chia Univ Dept Photon Taichung 40724 Taiwan Philips Elect Ltd Hong Kong Peoples R China

We reviewed our resent works using digital-signal-processing (DSP) techniques to improve visible-light-communication (VLC). A rolling-shutter-effect (RSE) light-panel and CMOS image-sensor based VLC and a visible-ligh... 详细信息

ISBN: (纸本)9781943580705

关键词： Digital signal processing

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Kalman-based Motion Estimation in Video Surveillance Systems for Safety applications

Kalman-based Motion Estimation in Video Surveillance Systems...

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conference on Real-Time image processing and Deep Learning

作者： Saponara, Sergio Univ Pisa Dept Informat Engn Via G Caruso 16 I-56122 Pisa Italy

ISBN: (纸本)9781510626584

The paper presents the design of a Kalman-based motion estimation algorithm to be used in video surveillance systems for safety applications, such as smoke and fire fast alarm generation. Particularly, the Kalman estimator, combined with a color detection method, allows detecting the presence of smoke and/or fire in video scenes. Hence, it is a key device for indoor and outdoor surveillance systems using video-cameras.

关键词： Smoke and fire detection Video and image signal processing Smart Camera Systems Real-Time Alarm Generation

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Deep convolutional neural networks based image fusion method using pyramid decomposition for medical applications

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AIP conference Proceedings 2023年第1期2477卷

作者： Suman Mishra Ramakishore Somala CMR Engineering College Hyderabad Telangana State India

In the current era of scientific expansion, medical imaging plays a significant role in numerous applications of health hazard analysis and treatment. In this regard, medical image fusion could be an efficient tool to combine multi modal images by using image processing techniques. The conventional approaches have failed to provide effective image quality assessments from the fused images. To overcome these drawbacks, in this work three stage hybrid fusion approach is developed by utilizing the combination of Laplacian and Gaussian pyramid decomposition on source image performed initially followed by generation of weight based Convolutional Neural Networks (CNN) approach. Finally, fusion of frequency bands is performed using pyramid reconstruction and utilizing the probabilistic fusion bands. The results obtained from the implementation shows that the proposed method outweighs the conventional approaches in the parameters of Peak signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), Connected Components (CC) and Structural Index Similarity (SSIM).

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A New Approximate Multiplier Design for Digital signal processing 13

A New Approximate Multiplier Design for Digital Signal Proce...

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13th IEEE International conference on ASIC

作者： Zhao, Yue Li, Tong Dong, Feng Wang, Qin He, Weifeng Jiang, Jianfei Shanghai Jiao Tong Univ Dept Micro Nano Elect Shanghai 200240 Peoples R China Beijing iQIYI Sci & Technol Co Ltd Shanghai Peoples R China

ISBN: (纸本)9781728107356

In this paper, a new approximate multiplier is proposed, which can decrease the multiplication complexity with the improved area and power performance by using OR and AND gates. To evaluate the efficiency of the proposed approximate multiplier, design parameters are compared with exact multiplier and recently proposed approximate designs. Experiment results reveal that the power consumption of the proposed approximate multiplier is only 32% of that in the exact multiplier. The proposed approximate multipliers are further evaluated in image sharpening and edge detection applications. The peak signal to noise ratio (PSNR) and structural similarity (SSIM) of our proposed approximate multipliers show that it can be used in image processing.

关键词： Approximate computing low power digital signal processing multiplier image processing

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Tight framelets on graphs for multiscale data analysis 18

Tight framelets on graphs for multiscale data analysis

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conference on wavelets and Sparsity xVIII

作者： Wang, Yu Guang Zhuang, xiaosheng Univ New South Wales Sch Math & Stat Sydney NSW Australia City Univ Hong Kong Dept Math Kowloon Tong Hong Kong Peoples R China

ISBN: (数字)9781510629707

ISBN: (纸本)9781510629707

In this paper, we discuss the construction and applications of decimated tight framelets on graphs. Based on graph clustering algorithms, a coarse-grained chain of graphs can be constructed where a suitable orthonormal eigen-pair can be deduced. Decimated tight framelets can then be constructed based on the orthonormal eigen-pair. Moreover, such tight framelets are associated with filter banks with which fast framelet transform algorithms can be realized. An explicit toy example of decimated tight framelets on a graph is provided.

关键词： Tight framelets framelets on graphs decimated framelets graph signal processing filter banks fast algorithms fast framelet transforms coarse-grained chain spectral graph theory graph Laplacian

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Bi-frequency 3D ghost imaging with Haar wavelet transform

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OPTICS ExPRESS 2019年第22期27卷 32349-32359页

作者： xi, Mengjia Chen, Hui Yuan, Yuan Wang, Gao He, Yuchen Liang, Yan Liu, Jianbin Zheng, Huaibin xu, Zhuo Xi An Jiao Tong Univ Elect Mat Res Lab Key Lab Minist EducSch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Int Ctr Dielect Res Sch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Inst Wide Band Gap Semicond Shaanxi Key Lab Informat Photon Tech Xian 710049 Shaanxi Peoples R China

Recently, ghost imaging has been attracting attention because its mechanism could lead to many applications inaccessible to conventional imaging methods. However, it is challenging for high-contrast and high-resolution imaging, due to its low signal-to-noise ratio (SNR) and the demand of high sampling rate in detection. To circumvent these challenges, we propose a ghost imaging scheme that exploits Haar wavelets as illuminating patterns with a bi-frequency light projecting system and frequency-selecting single-pixel detectors. This method provides a theoretically 100% image contrast and high-detection SNR, which reduces the requirement of high dynamic range of detectors, enabling high-resolution ghost imaging. Moreover, it can highly reduce the sampling rate (far below Nyquist limit) for a sparse object by adaptively abandoning unnecessary patterns during the measurement. These characteristics are experimentally verified with a resolution of 512 x 512 and a sampling rate lower than 5%. A high-resolution (1000 x 1000 x 1000) 3D reconstruction of an object is also achieved from multi-angle images. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： Computational imaging image processing Imaging techniques Optical imaging Three dimensional imaging x ray imaging

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Three-Dimensional CT image Reconstruction Techniques: Implementation and Comparison 3

Three-Dimensional CT Image Reconstruction Techniques: Implem...

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3rd International conference on Communications, signal processing, and their applications (ICCSPA)

作者： Sabah, Shafiya Dhou, Salam Amer Univ Sharjah Biomed Engn Grad Program Sharjah U Arab Emirates Amer Univ Sharjah Dept Comp Sci & Engn Biomed Engn Grad Program Biosci & Bioengn Res Inst Sharjah U Arab Emirates

ISBN: (纸本)9781728120850

High quality reconstructed images are a critical requirement in the field of medical imaging. Several attempts have been made by researchers to implement new techniques and to enhance present techniques. In this paper, we compared analytical ( simple and filtered back projection) and iterative reconstruction techniques based on different performance parameters including signal to noise ratio ( SNR), contrast to noise ratio ( CNR), reconstruction error, and computation time. xCAT phantom, a three-dimensional body digital phantom was used for the study where images are reconstructed from projections sampled with different sampling rates. Results showed that iterative technique provided much better reconstructed images in comparison to analytical techniques with a drawback in terms of longer computation time.

关键词： CT: computed tomography SBP: simple back projection FBP: filtered back projection ART: algebraic reconstruction technique SIRT: simultaneous iterative reconstruction techniques mGy: milligray mSv: millisievert SNR: signal to noise ratio CNR: contrast to noise ratio

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IR-FPA to miniaturized cameras - Configurable chip implementing analog and digital data-processing blocks 45

IR-FPA to miniaturized cameras - Configurable chip implement...

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conference on Infrared Technology and applications xLV

作者： Anchlia, Ankur Danda, Tejaswi Mittal, Saurabh Dayanandha, M. PeakSense Technol Beta BlockSigma Tech PkWhitefield Main Rd Bengaluru 560066 India

ISBN: (数字)9781510626706

ISBN: (纸本)9781510626706

This paper presents a system-on-chip solution that acts as a companion to infrared focal plane arrays (IR-FPAs), providing them with precision references, regulated power supplies, clocks and timing signals, as well as sampling analog or digital outputs for signal conditioning, correction and processing. To serve a wide variety of infrared imaging detectors, the chip is designed in a fully configurable manner that allows users to program specifications of signals going to an FPA and implement any custom signal correction, processing and application-specific algorithms.

关键词： Infrared FPA smart processing system-on-chip (SoC) infrared image signal processor (ISP)

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