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An Efficient High-Speed Lifting Based 1D/2D-DWT VLSI Architecture Using CDF-5/3 wavelet Transform For image processing applications

An Efficient High-Speed Lifting Based 1D/2D-DWT VLSI Archite...

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IEEE International conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)

作者： M Sushmitha S Chetan Sayantam Sarkar VLSI Design and Embedded Systems Dr. Ambedkar Institue of Technology Bengaluru India Dr. Ambedkar Institue of Technology Bengaluru India Vijaya Vittala Institue of Technology Bengaluru India

ISBN: (数字)9781728197722

ISBN: (纸本)9781728197739

There are various Discrete wavelet Transform architectures that are designed to fulfil certain requirements and criteria's. The convolution method which is an old traditional method which requires more multipliers, hardware resources and huge memory storage which is not apt to yield high speed and efficient image processing, signal processing application designs when compared to lifting method. In this paper, we have proposed an architecture for lifting scheme based CDF-5/3 2D-DWT, which includes less mathematical computations and high speed is achieved compared to existing works. The proposed architecture design is multiplier-less and utilizes lesser number of components hence it is area efficient and also achieves high throughput rate. The RTL of this design is described in VHDL language and is synthesized in Xilinx 14.5 and target device is Virtex-5 series XC5VLX110T for testing the resulting parameters like LUTs, flip-flops and slices. Higher PSNR values and lesser MSE values are achieved when tested for different kind of images. The maximum operating frequency achieved for the designed 2D-DWT architecture is 258.358MHz. Hence the proposed 2D-DWT architecture has increased speed, less computational complexity and good hardware utilization when compared to other existing works.

关键词： Discrete wavelet transforms Finite impulse response filters image coding Two dimensional displays Very large scale integration Convolution Clocks

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Emboli Detection by machine learning algorithms using multi-level feature extraction

Emboli Detection by machine learning algorithms using multi-...

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International conference on image and signal processing and their applications (ISPA)

作者： Ab Waheed Lone Ahmet Elbir Nizamettin Aydin Department of Computer Engineering Yildiz Technical University Istanbul Turkey Department of Computer Engineering Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

In real world, data understanding involves finding relationship between dependent and independents events, and usually this data is embedded in the form of images, audio, videos, speech, text and much more and to extract useful and representative information, feature extraction and representation is a front-end step. For machine learning algorithms, feature extraction is a preprocessing technique that helps in finding the relationship between different variables. In biomedical signal analysis such as cerebral emboli signal detection, feature extraction from samples constitutes an important step. In this paper, we performed two step feature extraction procedure. First we extracted Mel Frequency Cepstral Coefficients (MFCC) and biologically inspired Gamma-tone Cepstral Coefficients from Doppler signals. Second we extracted kurtosis and skewness parameters from all the Mel-frequency cepstral coefficients and Gamma-tone Cepstral Coefficients coefficients. To gain the understanding of extracted features from Doppler signals, we trained some machine learning algorithms such as k-nearest neighbors, support vector machines and logistic regression. GTCC based kurtosis and skewness features show better classification between emboli, artifact signals and Doppler speckle signals. We present evaluation results using confusion matrix for classification between emboli signals (ES), Doppler speckle (DS) and artifact signals (AS).

关键词： wavelet transforms Machine learning algorithms Scattering Pattern classification Machine learning Speckle Feature extraction

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A fast algorithm for the Bayesian adaptive lasso

A fast algorithm for the Bayesian adaptive lasso

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European signal processing conference (EUSIPCO)

作者： Athanasios A. Rontogiannis Konstantinos E. Themelis Konstantinos D. Koutroumbas Institute for Space Applications and Remote Sensing National Observatory of Athens Penteli Greece

This paper presents a novel hierarchical Bayesian model which allows to reconstruct sparse signals using a set of linear measurements corrupted by Gaussian noise. The proposed model can be considered as the Bayesian counterpart of the adaptive lasso criterion. A fast iterative algorithm, which is based on the type-ii maximum likelihood methodology, is properly adjusted to conduct Bayesian inference on the unknown model parameters. The performance of the proposed hierarchical Bayesian approach is illustrated on the reconstruction of both sparse synthetic data, as well as real images. Experimental results show the improved performance of the proposed approach, when compared to state-of-the-art Bayesian compressive sensing algorithms.

关键词： Bayesian methods Adaptation models image reconstruction signal processing algorithms Vectors Compressed sensing Inference algorithms

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Inspection and analysis of the walls of fluid filled tubes by active electrolocation - a biomimetic approach

Inspection and analysis of the walls of fluid filled tubes b...

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conference on Bioinspiration, Biomimetics, and Bioreplication

作者： Gottwald, Martin Mayekar, Kavita Reiswich, Vladislav Bousack, Herbert Damalla, Deepak Biswas, Shubham Metzen, Michael G. von der Emde, Gerhard Univ Bonn Inst Zool Endenicher Allee 11-13 D-53115 Bonn Germany Forschungszentrum Julich Inst Bio & Nnaosyst D-52425 Julich Germany

ISBN: (纸本)9780819485373

During their nocturnal activity period, weakly electric fish employ a process called "active electrolocation" for navigation and object detection. They discharge an electric organ in their tail, which emits electrical current pulses, called electric organ discharges (EOD). Local EODs are sensed by arrays of electroreceptors in the fish's skin, which respond to modulations of the signal caused by nearby objects. Fish thus gain information about the size, shape, complex impedance and distance of objects. Inspired by these remarkable capabilities, we have designed technical sensor systems which employ active electrolocation to detect and analyse the walls of small, fluid filled pipes. Our sensor systems emit pulsed electrical signals into the conducting medium and simultaneously sense local current densities with an array of electrodes. Sensors can be designed which (i) analyse the tube wall, (ii) detect and localize material faults, (iii) identify wall inclusions or objects blocking the tube (iv) and find leakages. Here, we present first experiments and FEM simulations on the optimal sensor arrangement for different types of sensor systems and different types of tubes. In addition, different methods for sensor read-out and signal processing are compared. Our biomimetic sensor systems promise to be relatively insensitive to environmental disturbances such as heat, pressure, turbidity or muddiness. They could be used in a wide range of tubes and pipes including water pipes, hydraulic systems, and biological systems. Medical applications include catheter based sensors which inspect blood vessels, urethras and similar ducts in the human body.

关键词： active electrolocation electroreceptor electric image object detection material analysis coronary plaque blood vessel

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Comparison of higher order diffusion filters for speckle noise reduction

Comparison of higher order diffusion filters for speckle noi...

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International conference on Computer applications and Industrial Electronics (ICCAIE)

作者： Ch. Kranthi Rekha V. Vijaya B. Sreedevi LUC Mantin Malaysia Vijay College of Engineering for Women VCEW India

Visual information transmitted in the form of digital images is becoming a major method of communication in the modern age, but the image obtained after transmission is often corrupted with noise. The received image needs processing before it can be used in the applications. image denoising involves the manipulation of the image data to produce a visually high quality image. This thesis reviews the existing denoising algorithms, such as filtering approach, wavelet based approach, and multifractal approach, and performs their comparative study. Different noise models including additive and multiplicative types are used. They include Gaussian noise, salt and pepper noise, speckle noise and Brownian noise. Selection of the denoising algorithm is application dependent. Hence, it is necessary to have knowledge about the noise present in the image so as to select the appropriate denoising algorithm. The filtering approach has been proved to be the best when the image is corrupted with salt and pepper noise. The Partial differential equation approach finds applications in denoising images corrupted with Gaussian noise. In the case where the noise characteristics are complex, the multi fractal approach can be used. A quantitative measure of comparison is provided by the signal to noise ratio of the image. Aim of the project is to reduce the speckle noise from the medical images by retaining most of the information, using fourth order partial differential equations and comparing the results with second order partial differential equation method, that is best suitable for a medical practitioner or a doctor to diagnose well by comparing this denoised image with the obtained.

关键词： Adaptive filters Speckle PSNR Filtering theory Partial differential equations image edge detection

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Enterprise crowdsourcing platform for geospatial image analysis

Enterprise crowdsourcing platform for geospatial image analy...

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IEEE signal processing and Communications applications (SIU)

作者： Fatih Kahraman Cengiz Hüroğlu Mümin İmamoğlu Büşra Y. Özcan Muhammed İ. Kalkan Muhammet A. Hocaoğlu Ergin Öztürk Binnur Kurt TÜBİTAK BİLGEM BTE Kocaeli Türkiye Omega Eğitim ve Danışmanlık İstanbul Türkiye

Although today's computing systems present powerful solutions to process big data with the help of recent advances in cloud computing technologies, many problems remain unsolved due to lack of acceptable algorithms. For instance, searching for a lost plane or damage assessment after earthquake on a high-resolution remote sensing satellite image are unsolved problems. In recent years, in order to solve such unsolved problems, a group of expert and nonexpert people called crowd is utilized. An expert in the group is not expected to solve whole problem. Instead, geospatial image is partitioned in space and each expert in the pool studies the partition assigned to him/her. The solution to the original problem is obtained by merging the partial solutions. There are two open issues: i) How to partition the space and how to distribute the partitions to the crowd ii) How to merge the partial solutions. In this study, we devise several algorithms to address these issues, introduce our web-based platform, and crowd-sourcing implementation.

关键词： Crowdsourcing Geospatial analysis Remote sensing Java image analysis Big data

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Edgeworth-based approximation of Mutual Information for medical image registration

Edgeworth-based approximation of Mutual Information for medi...

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Workshops on image processing Theory, Tools and applications, IPTA

作者： Mathieu Rubeaux Jean-Claude Nunes Laurent Albera Mireille Garreau LTSI Université de Rennes 1 France UMR 642 INSERM Rennes France

Mutual Information (MI) has been extensively used as a similarity measure in image registration and motion estimation, and it is particularly robust for 3D multimodal medical image registration. However, MI estimators are known i) to have a high variance and ii) to be computationally costly. In order to overcome these drawbacks, we propose a new similarity measure based on an Edgeworth-based third order expansion of MI and named 3-EMI in the following. This kind of approximation is well known in signal processing, and especially in Independent Components Analysis (ICA), but its computation is easier since data can be prewhitened contrary to images in registration. The performance of affine and non-rigid registrations based on the 3-EMI metric is studied through computer results in the context of cardiac multislice computed tomography. In fact, an estimate of the 3-EMI metric using sample statistics is compared to a histogram-based estimate of the standard normalized MI, showing a better robustness of the 3-EMI measure with respect to the range of the searched deformation. In addition, in practice, one part of the floating image may be missing regarding the reference image. Computer results show that our approach is less sensitive to such a practical problem.

关键词： Approximation methods image registration Measurement Joints Biomedical imaging Random variables image edge detection

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Scale Space and Variational Methods in Computer Vision 1

Scale Space and Variational Methods in Computer Vision

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丛书名： Lecture Notes in Computer Science

1000年

作者： Tatiana A. Bubba Romina Gaburro Silvia Gazzola Kostas Papafitsoros Marcelo Pereyra Carola-Bibiane Schönlieb

ISBN: (数字)9783031923661

ISBN: (纸本)9783031923654

The two-volume set LNCS 15667 and 15668 constitutes the proceedings of the 10th International conference on Scale Space and Variational Methods in Computer Vision, SSVM 2025, which took place in Dartington, UK, in May 2025. The total of 63 full papers accepted in the proceedings were carefully reviewed and selected from 81 submissions. They were organized in topical sections as follows: Part I: Inverse Problems in Imaging; machine and deep learning in imaging; Part ii: Optimization for imaging: theory and methods; scale space, PDES, flow, motion and registration.

关键词： Computer Imaging, Vision, Pattern Recognition and Graphics signal, image and Speech processing Computer Communication Networks Computer applications Machine Learning Mathematics of Computing

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Remote sensing and acoustic telemetry

Remote sensing and acoustic telemetry

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OCEANS

作者： D. Green T. Nguyen Benthos Inc. North Falmouth MA USA ECE Department University of California San Diego CA USA

There is a growing need for remote underwater sensing and imaging without the burden of cabled connectivity to the outside world, and the best method for achieving this is with acoustic communications. However, the acoustic link is only one aspect of the problem, as the sensor system needs to interface with the modem, and perhaps with intermediary subsystems to provide some level of data pre-processing. We are developing an integrated processor/modem capability to provide the sensor developer with much of the signal processing capability needed to prepare and store sensor-level data, and to transmit information and receive commands as required. Our prototype development for such a system is focused on still-frame image compression and transmission in support of robotic crawlers in a mine-countermeasure (MCM) mission. image compression is based on novel wavelet-based algorithms developed in part by the University of California at San Diego (UCSD). The robotic crawlers are a development of Foster-Miller Inc. and the Naval Coastal Systems Station. Benthos provides the acoustic and RF links for command and control and image/sensor transmission. The sensor computer which performs the image compression is a micro-PC with extensive capabilities for R and D applications, including sensor-level data processing, in-situ data fusion, and connectivity to the modem. The modem currently supports signaling up to 2400 bps (raw data rate), although 100 bps to 800 bps are more likely to be used in other than vertical channels. We show examples of full and compressed images, the latter as received via an acomms-to-RF modem gateway buoy. Enhancements expected include incorporation of much higher data rate signaling methods, and customized signal processing for raw sensor-level data.

关键词： Remote sensing Telemetry Modems image coding Underwater acoustics Acoustic sensors Robot sensing systems Crawlers image sensors signal processing

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TCIE-ResNeXtGAN: infrared and water vapor satellite image fusion model using dual discriminator generative adversarial networks and ResNeXt for improving tropical cyclone intensity estimation accuracy

TCIE-ResNeXtGAN: infrared and water vapor satellite image fu...

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2022 conference on Infrared, Millimeter, Terahertz Waves and applications, IMT 2022

作者： Guo, Jia-Xu Zhang, Chang-Jiang College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China Taizhou University Taizhou318000 China

ISBN: (纸本)9781510662476

Different characteristics of satellite images are reflected in different channels, so the monitoring and early warning of meteorological disasters based on satellite image data of a single channel may not achieve satisfactory results. The infrared channel satellite image reflects the ground and cloud top infrared radiation or the temperature distribution. The water vapor channel satellite image reflects the spatial distribution of water vapor in the upper atmosphere. The two channel satellite images reflect atmospheric characteristics from different wavebands. This paper proposes an infrared and water vapor channel satellite image fusion model (TCIE-ResNeXtGAN) based on dual discriminator generative adversarial network and ResNeXt to improve the accuracy of tropical cyclone (Tropical Cyclone, TC) intensity estimation. For this reason, we define the factors affecting TC intensity estimation, namely the brightness temperature gradient in satellite images, based on our previous work, and introduce it to the loss function in the proposed deep learning model to guide the training process of the model. In this way, the purpose of improving the estimation accuracy of TC intensity using fused satellite images is achieved. To demonstrate the effectiveness of the fusion results in this paper, we compare performance between the existing three models and our model. The experimental results show that the proposed image fusion method in this paper can preserve the infrared and water vapor dual-channel information to the greatest extent, while improving the estimation accuracy of TC intensity using fused satellite image. © 2023 SPIE.

关键词： Generative adversarial networks

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