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IEEE International Ultrasonics Symposium

作者： Dimitris Perdios Manuel Vonlanthen Adrien Besson Florian Martinez Marcel Arditi Jean-Philippe Thiran École Polytechnique Fédérale de Lausanne Signal Processing Laboratory (LTS5) Lausanne Switzerland

The problem of improving image quality in ultrafast ultrasound (US) imaging by means of regularized iterative algorithms has raised a vast interest in the US community. These approaches usually rely on standard image processing priors, such as wavelet sparsity, which are of limited efficacy in the context of US imaging. Moreover, the high computational complexity of iterative approaches make them difficult to deploy in real-time applications. We propose an approach which relies on a convolutional neural network trained exclusively on a simulated dataset for the purpose of improving images reconstructed from a single plane wave (PW) insonification. We provide extensive results on numerical and in vivo data from the plane wave imaging challenge (PICMUS). We show that the proposed approach can be applied in real-time settings, with an increase in contrast-to-noise ratio of more than 8.4 dB and an improvement of the lateral resolution by at least 25 %.

关键词： image reconstruction Radio frequency Training image resolution Speckle Phantoms

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Hierarchical Segmentation Based Upon Multi-resolution Approximations and the Watershed Transform 13th

Hierarchical Segmentation Based Upon Multi-resolution Approx...

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13th International Symposium on Mathematical Morphology (ISMM)

作者： Figliuzzi, Bruno Chang, Kaiwen Faessel, Matthieu PSL Res Univ Mines ParisTech Ctr Math Morphol Paris France

ISBN: (纸本)9783319572406;9783319572390

image segmentation is a classical problem in image processing, which aims at defining an image partition where each identified region corresponds to some object present in the scene. The watershed algorithm is a powerful tool from mathematical morphology to perform this specific task. When applied directly to the gradient of the image to be segmented, it usually yields an over-segmented image. To address this issue, one often uses markers that roughly correspond to the locations of the objects to be segmented. The main challenge associated to marker-controlled segmentation becomes thus the determination of the markers locations. In this article, we present a novel method to select markers for the watershed algorithm based upon multi-resolution approximations. The main principle of the method is to rely on the discrete decimated wavelet transform to obtain successive approximations of the image to be segmented. The minima of the gradient image of each coarse approximation are then propagated back to the original image space and selected as markers for the watershed transform, thus defining a hierarchical structure for the detected contours. The performance of the proposed approach is evaluated by comparing its results to manually segmented images from the Berkeley segmentation database.

关键词： Watershed transform Multi-resolution approximations Hierarchical segmentation wavelet transform

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Application of Distributed Arithmetic in image and ECG signal processing 3

Application of Distributed Arithmetic in Image and ECG Signa...

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International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC)

作者： Sunny, Anu Mary Jacob, Naveen Viswajyothi Coll Engn & Technol Dept Elect & Commun Engn Vazhakulam Kerala India

ISBN: (纸本)9781538632437

The core of many DSP applications involve convolution which was previously implemented by Multiply and Accumulate operations or MAC. It requires a number of multipliers and accumulators. The use of multipliers and accumulators result in faster execution but it also results in an increase in cost. Also the number of multipliers and adders are limited. Hence a new technique known as Distributed Arithmetic (DA) was proposed. It is basically a multiplier-less concept utilizing Lookup Table (LUT). It is used when one of the operand is fixed. The input enters into a serial register which is used to access the LUT. To get the address from the LUT we consider the bit positions and get the values of inputs by that bit position. The output from the lookup table is shifted accordingly and the shifted results are added together to form the final result. Hence it basically involves accessing the lookup table, shift and add operation. After implementing the DA logic and comparing it with the convolution scheme, we apply this concept in Discrete wavelet Transform (DWT) of an image and ECG signal by using Haar filter coefficient.

关键词： Distributed Arithmetic Discrete wavelet Transform ECG signal

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Low Area & Memory Efficient VLSI Architecture of 1D/2D DWT for Real Time image Decomposition

Low Area & Memory Efficient VLSI Architecture of 1D/2D DWT f...

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International Symposium on Electronic System Design (ISED)

作者： Anirban Chakraborty Ayan Banerjee Department of Electronics & Tele-communication Engineering Indian Institute of Engineering Science and Technology Shibpur Howrah India

ISBN: (纸本)9781538665763;9781538665756

There is a dearth of high quality reconfigurable hardware for DWT which can be extensively used in various real time signal and image processing applications. In this article, we have focused on proposing a dedicated customizable hardware for DWT applicable to 1D/2D signal processing. We have proposed bit-serial Distributed Arithmetic (DA) based VLSI architectures for ID/2D DWT. Exploitation of DA enables us to make our designs Multiplierless, thereby consuming less area. Bit serial configuration of DA is also exploited to introduce modularity and pipelining in the proposed convolution DWT based 1D/2D architectures. Though the speed of the proposed designs may not be suitable for certain applications, a number of parallel channels can be introduced for the same. The provision of mode selection can efficiently be used to realize 9/7 and also 5/3 DWT filters in the same proposed architecture. In the proposed 1D/2D architecture, we have achieved about 50% memory size reduction, 30% reduction in area consumption and comparable speed in comparison to the other latest notable DWT architecture so far. We have verified the viability of our proposed 2D architecture by utilizing it in real time image decomposition.

关键词： Discrete wavelet transforms Low pass filters Read only memory Memory management Adders Two dimensional displays

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Fractional wavelet scattering network and applications

arXiv

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arXiv 2018年

作者： Liu, Li Wu, Jiasong Li, Dengwang Senhadji, Lotfi Shu, Huazhong Ministry of Education Nanjing210096 China International Joint Laboratory of Information Display and Visualization Nanjing210096 China Nanjing210096 China INSERM U1099 Rennes35000 France Université de Rennes 1 Rennes35000 France Rennes35000 France Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and Electronics Shandong Normal University Jinan250014 China

Objective: The present study introduces a fractional wavelet scattering network (FrScatNet), which is a generalized translation invariant version of the classical wavelet scattering network (ScatNet). Methods: In our approach, the FrScatNet is constructed based on the fractional wavelet transform (FRWT). The fractional scattering coefficients are iteratively computed using FRWTs and modulus operators. The feature vectors constructed by fractional scattering coefficients are usually used for signal classification. In this work, an application example of FrScatNet is provided in order to assess its performance on pathological images. Firstly, the FrScatNet extracts feature vectors from patches of the original histological images under different orders. Then we classify those patches into target (benign or malignant) and background groups. And the FrScatNet property is analyzed by comparing error rates computed from different fractional orders respectively. Based on the above pathological image classification, a gland segmentation algorithm is proposed by combining the boundary information and the gland location. Results: The error rates for different fractional orders of FrScatNet are examined and show that the classification accuracy is significantly improved in fractional scattering domain. We also compare the FrScatNet based gland segmentation method with those proposed in the 2015 MICCAI Gland Segmentation Challenge and our method achieves comparable results. Conclusion: The FrScatNet is shown to achieve accurate and robust results. More stable and discriminative fractional scattering coefficients are obtained by the FrScatNet in this work. Significance: The added fractional order parameter is able to analyze the image in the fractional scattering domain. Copyright © 2018, The Authors. All rights reserved.

关键词： Classification (of information)

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Medical image fusion techniques based on combined discrete transform domains 34

Medical image fusion techniques based on combined discrete t...

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34th National Radio Science Conference, NRSC 2017

作者： El-Hoseny, Heba M. Elrabaie, El-Sayed M. Elrahman, Wael Abd El-Samie, Fathi E. Abd Department of Electrical Engineering Faculty of Engineering Benha University Egypt Department of Electronics and Electrical Communications Faculty of Electronic Engineering Menoufia University Egypt

ISBN: (纸本)9781509046096

This paper investigates some of medical image fusion techniques and discusses the most important advantages and disadvantages of these techniques to develop hybrid techniques that enhance the fused image quality. Both traditional and hybrid fusion algorithms are evaluated using several quality metrics including average gradient, local contrast, standard deviation, edge intensity, entropy, structure similarity index, universal image quality index, feature similarity index, Peak signal-to-Noise Ratio (PSNR), mutual information, Qab/f, and processing time. Experimental results prove that the hybrid technique of Additive wavelet Transform (AWT) and Dual Tree complex wavelet transform (DT-CWT) with high pass sharpening filter provides the best fused images of highest quality, highest details, shortest processing time, and best visualization. This is favourable, especially for helping in accurate diagnosis and optimal therapy applications. © 2017 IEEE.

关键词： Discrete wavelet transforms

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Toward high-intensity focused ultrasound lesion quantification using compressive sensing theory

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE 2017年第12期231卷 1152-1164页

作者： Ghasemifard, Hadi Behnam, Hamid Tavakkoli, Jahan Islamic Azad Univ Tehran Sci & Res Branch Dept Biomed Engn Tehran Iran Iran Univ Sci & Technol Sch Elect Engn Dept Biomed Engn Tehran *** Iran Ryerson Univ Dept Phys Toronto ON Canada St Michaels Hosp Inst Biomed Engn Sci & Technol iBEST Keenan Res Ctr Biomed Sci Toronto ON Canada

Compressive sensing theory has in recent years been increasingly used in various pattern recognition applications. Compressive sensing theory makes it possible, under certain assumptions, to recover a signal or an image sampled below the Nyquist sampling limit. In this work, a new application of compressive sensing based on the threshold algorithm, in the area of controlling and monitoring of high-intensity focused ultrasound therapy, was investigated. In this work, a new method of high-intensity focused ultrasound lesion detection is presented based on a modified compressive sensing method in combination with the threshold algorithm and the wavelet transforms. In this study, analysis of the suggested method is performed using two sets of data: simulated and experimental ultrasound radio frequency data. The results of processing the data show that the proposed algorithm results in enhancement of the high-intensity focused ultrasound lesion contrast in comparison with the ultrasound B-mode and standard compressive sensing imaging methods. The results of the study show that the modified compressive sensing method could effectively detect thermal lesions in vitro. Comparing the estimated size of the thermal lesion (8.3mmx8.4mm) using the proposed algorithm with the actual size of that from physical examination (10.1mmx9mm) shows that we could detect high-intensity focused ultrasound thermal lesions with the difference of 0.8mmx0.5mm.

关键词： High-intensity focused ultrasound compressive sensing radio frequency signal sparse representation wavelet transform

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Using wavelet transforms to suppress light interference in the optoelectronic monitoring system of the weft thread break

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Journal of Physics: Conference Series 2019年第1期1327卷

作者： Yu Yu Morgunov A G Yakunin Master student Altai State Technical University Barnaul Russia Head of chair Altai State Technical University Barnaul Russia

The article presents the results of studies on interference suppression in optoelectronic methods for monitoring weft thread weaving looms on the basis of linear image sensors caused by inhomogeneities of the background created by sources of natural or artificial light sources in a controlled image scene. Existing solutions that use linear or nonlinear filtering are focused primarily on the processing of two-dimensional images on personal computers and are unsuitable for use in embedded applications. In particular, their use is also ineffective for solving the above problem, when the useful signal is defined as the difference between the output signals of the photodetector taken at a fixed time interval. As studies have shown, in this case, the best result is the use of discrete wavelet-transform.

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Grid impedance estimation using low power signal injection in noisy measurement condition based on wavelet denoising 3

Grid impedance estimation using low power signal injection i...

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3rd Iranian Conference on signal processing and Intelligent Systems, ICSPIS 2017

作者： Nezhadi, Mohammad. M. Alyan Hassanpour, Hamid Zare, Firuz Image Processing and Data Mining Lab Shahrood University of Technology Shahrood Iran Power Engineering Group University of Queensland QLD Australia

ISBN: (纸本)9781538649725

Grid impedance estimation is used in many power system applications such as power quality analysis of smart grids and grid connected renewable energy systems. In this paper a low power and high frequency range signal injected to grid, and the ratio of voltage to current signal is calculated as impedance. Accuracy of impedance estimation in noiseless systems is independent to energy of injected signal. However, in noisy system, energy of injected signal must be sufficient for an accurate approximation. In this paper, two groups of noise (source harmonic voltage noise and measurement noise) are considered. The additive white Gaussian noise is assumed as the measurement noise. In this paper, we proposed to denoising the current and voltage signals using stationary wavelet denoising without increasing the energy of the injected signal. The injection signal is a short duration rectangular pulse. Accurate impedance estimation using signal injection can be done in frequencies that the energy of signal is bigger enough than the energy of noise. The simulation results show that the proposed method can properly estimate grid impedance in a wide frequency range 2 kHz to 150 kHz. © 2017 IEEE.

关键词： Frequency response

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A robust blind 3-D mesh watermarking based on wavelet transform for copyright protection 3

A robust blind 3-D mesh watermarking based on wavelet transf...

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3rd International Conference on Advanced Technologies for signal and image processing, ATSIP 2017

作者： Hamidi, Mohamed Haziti, Mohamed El Cherifi, Hocine Aboutajdine, Driss Assoct. Unit to the CNRST-URAC N 29 Faculty of Sciences University of Mohammed v RabatBP 1014 Morocco Higher School of Technology Sale Morocco UMR 6306 CNRS University of Burgundy Dijon France

ISBN: (纸本)9781538605516

Nowadays, three-dimensional meshes have been extensively used in several applications such as, industrial, medical, computer-aided design (CAD) and entertainment due to the processing capability improvement of computers and the development of the network infrastructure. Unfortunately, like digital images and videos, 3-D meshes can be easily modified, duplicated and redistributed by unauthorized users. Digital watermarking came up while trying to solve this problem. In this paper, we propose a blind robust watermarking scheme for three-dimensional semiregular meshes for Copyright protection. The watermark is embedded by modifying the norm of the wavelet coefficient vectors associated with the lowest resolution level using the edge normal norms as synchronizing primitives. The experimental results show that in comparison with alternative 3-D mesh watermarking approaches, the proposed method can resist to a wide range of common attacks, such as similarity transformations including translation, rotation, uniform scaling and their combination, noise addition, Laplacian smoothing, quantization, while preserving high imperceptibility. © 2017 IEEE.

关键词： Digital watermarking

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