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International Conference on signal, image, Vision and their applications (SIVA)

作者： Khelil, K. Bouadjila, T. Berrezzek, F. Univ Souk Ahras Fac Sci & Tec LEER Lab Souk Ahras 41000 Algeria

ISBN: (纸本)9781538671207

The objective of multiple description coding (MDC) is to encode a single information source into multiple bitstreams, in a manner that the reconstructed source can be produced at different qualities according to the amount of bitstreams received at the decoder. In this paper, we propose to employ an optimal filtering strategy as a post processing method for a multiple description transform coding (MDTC) approach which utilizes discrete wavelet transform (DWT). Experimental results show that the proposed approach provides better results compared to existing approaches in the literature.

关键词： Multiple description transform coding optimal filtering discrete wavelet transform post-processing

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Staistical features extraction in wavelet domain for texture classification

Staistical features extraction in wavelet domain for texture...

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

作者： Soraya ZEHANI Abdeldjalil OUAHABI Malika MIMI Abdelmalik TALEB-AHMED Electrical Engineering department Biskra University Biskra Algeria Polytech Tours Imaging and Brain University of Tours Tours France Electrical Engineering department Mostaganem University Mostaganem Algeria IEMN DOAE UMR CNRS 8520 UPHF Valenciennes France

ISBN: (纸本)9781728131573

This paper presents a new approach for texture classification generalizing a well-known statistical features combining the fractal analysis by means of fractal dimension (FD) with the selection first and second order statistics features in the spatial and wavelet domain. The objective of our paper is to propose the features extraction using statistical parameters in the spatial domain and in wavelet domain with different wavelets, with and without preprocessing stage for the texture classification using neural networks for pattern recognition and studying the effect of the preprocessing and wavelets in classification accuracy. The extracted features are used as the input of the ANN classifier. The performance of the proposed methods are evaluated by using two classes of Brodatz database textures. Finally, classification assessment measures such as the confusion matrix, ROC curves and accuracy are applied to the proposed methods.

关键词： Artificial neurals network (ANN) Discrete wavelet transform (DWT) Fractal dimension (FD) Preprocessing Statistical features extraction Texture analysis Feature extraction wavelet domain texture analysis Pretreatment Taxonomy wavelets texture textures fractal analysis spatial domain

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Approximate Computing Based Adder Design for DWT Application 23rd

Approximate Computing Based Adder Design for DWT Application

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23rd International Symposium on VLSI Design and Test

作者： Acharya, Moumita Basu, Samik Behera, Biranchi Narayan Chakrabarti, Amlan Univ Calcutta Inst Radio Phys & Elect 92 APC Rd Kolkata 700009 India CV Raman Collage Engn Elect & Tele Commun Engn Dept Bhubaneswar 752054 India Univ Calcutta AK Choudhury Sch Informat Technol 92 APC Rd Kolkata 700009 India

ISBN: (纸本)9789813297661;9789813297678

Approximate computing is gaining popularity in hardware design of different application circuits. The bit-width reduction in approximate computing reduces the power requirement and chip area though it introduces error in the processed output. In this paper, we have proposed approximate computing based various designs of approximation of mirror adder (MA) circuit, which can be used to implement discrete wavelet transform (DWT) hardware for various image processing applications. We have also used voltage-scaling approach in our design, which reduces the power requirement appreciably. We have studied four levels of approximation of mirror adder and among them the fourth level of approximation is tested and justified for the design application. The goodness of our design is well justified as it shows marginal reduction in signal to noise ratio with a good reduction of layout area and power. We have used 180 nm technology node in our proposed ASIC design.

关键词： Approximate computing Adder Voltage scaling DWT image compression

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Temporal Scalability of Dynamic Volume Data Using Mesh Compensated wavelet Lifting

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IEEE TRANSACTIONS ON image processing 2018年第1期27卷 419-431页

作者： Schnurrer, Wolfgang Pallast, Niklas Richter, Thomas Kaup, Andre Friedrich Alexander Univ Erlangen Nurnberg Chair Multimedia Commun & Signal Proc D-91058 Erlangen Germany

Due to their high resolution, dynamic medical 2D+t and 3D+t volumes from computed tomography (CT) and magnetic resonance tomography (MR) reach a size which makes them very unhandy for teleradiologic applications. A lossless scalable representation offers the advantage of a down-scaled version which can be used for orientation or previewing, while the remaining information for reconstructing the full resolution is transmitted on demand. The wavelet transform offers the desired scalability. A very high quality of the lowpass sub-band is crucial in order to use it as a down-scaled representation. We propose an approach based on compensated wavelet lifting for obtaining a scalable representation of dynamic CT and MR volumes with very high quality. The mesh compensation is feasible to model the displacement in dynamic volumes which is mainly given by expansion and contraction of tissue over time. To achieve this, we propose an optimized estimation of the mesh compensation parameters to optimally fit for dynamic volumes. Within the lifting structure, the inversion of the motion compensation is crucial in the update step. We propose to take this inversion directly into account during the estimation step and can improve the quality of the lowpass sub-band by 0.63 and 0.43 dB on average for our tested dynamic CT and MR volumes at the cost of an increase of the rate by 2.4% and 1.2% on average.

关键词： Scalability discrete wavelet transforms motion compensation computed tomography magnetic resonance tomography signal analysis

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Graph signal processing for visual analysis and data exploration

Graph signal processing for visual analysis and data explora...

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作者： Paola Tatiana Llerena Valdivia UNIVERSIDADE DE SAO PAULO

学位级别：博士

signal processing is used in a wide variety of applications, ranging from digital image processing to biomedicine. Recently, some tools from signal processing have been extended to the context of graphs, allowing its use on irregular domains. Among others, the Fourier Transform and the wavelet Transform have been adapted to such context. Graph signal processing (GSP) is a new field with many potential applications on data exploration. In this dissertation we show how tools from graph signal processing can be used for visual analysis. Specifically, we proposed a data filtering method, based on spectral graph filtering, that led to high quality visualizations which were attested qualitatively and quantitatively. On the other hand, we relied on the graph wavelet transform to enable the visual analysis of massive time-varying data revealing interesting phenomena and events. The proposed applications of GSP to visually analyze data are a first step towards incorporating the use of this theory into information visualization methods. Many possibilities from GSP can be explored by improving the understanding of static and time-varying phenomena that are yet to be uncovered.

关键词： Visual analysis Graph signal processing Information visualization Graph wavelet transform

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International Conference on signal processing and Communication, ICSC 2018

International Conference on Signal Processing and Communicat...

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International Conference on signal processing and Communication, ICSC 2018

ISBN: (纸本)9789811325526

The proceedings contain 61 papers. The special focus in this conference is on signal processing and Communication. The topics include: Slot integrated folded substrate integrated waveguide bandpass filter for K band applications;Mutation-based bee colony optimization algorithm for near-ML detection in GSM-MIMO;novel substrate-integrated waveguide incorporated with band-pass filter;PAPR reduction analysis of OFDM systems using GA-, PSO-, and ABC-based PTS techniques;an active polarization-insensitive ultrathin metamaterial absorber with frequency controllability;the internet of things: A vision for smart world;special pedestrian and head pose detection for autonomous vehicles;sorted outlier detection approach based on silhouette coefficient;recent trends in IoT and its requisition with IoT built engineering: A review;the terrain’s discrimination criterion for the lengthened objects identification;effective way to simulate the radar’s signal multi-path propagation;distributed arithmetic based hybrid architecture for multiple transforms;real-time video surveillance for safety line and pedestrian breach detection in a dynamic environment;human activity recognition in video benchmarks: A survey;SITO type voltage-mode biquad filter based on single VDTA;despeckling of medical ultrasound images using fast bilateral filter and neighShrinkSure filter in wavelet domain;density-based approach for outlier detection and removal;an improved design technique of digital finite impulse response filter for notch filtering;leakage reduction in full adder circuit using source biasing at 45 nm technology;mathematical analysis of commonly used feeding techniques in rectangular microstrip patch antenna;Dual-mode quadrature oscillator based on single FDCCII with all grounded passive components;Hybrid color image watermarking algorithm based on DSWT-DCT-SVD and Arnold transform.

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Robust tracking of multiple objects in video by adaptive fusion of subband particle filters

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IET COMPUTER VISION 2018年第8期12卷 1207-1218页

作者： Mahmoud, Ahmed Sherif, Sherif S. Univ Manitoba Dept Elect & Comp Engn 75 Chancellors Circle Winnipeg MB R3T 5V6 Canada

Tracking of moving objects in video sequences is an important research problem because of its many industrial, biomedical, and security applications. Significant progress has been made on this topic in the last few decades. However, the ability to track objects accurately in video sequences that have challenging conditions and unexpected events, e.g. background motion and shadows;objects with different sizes and contrasts;a sudden change in illumination;partial object camouflage;and low signal-to-noise ratio, remains an important research problem. To address such difficulties, the authors developed a robust multiscale visual tracker that represents a captured video frame as different subbands in the wavelet domain. It then applies N independent particle filters to a small subset of these subbands, where the choice of this subset of wavelet subbands changes with each captured frame. Finally, it fuses the outputs of these N independent particle filters to obtain final position tracks of multiple moving objects in the video sequence. To demonstrate the robustness of their multiscale visual tracker, they applied it to four example videos that exhibit different challenges. Compared to a standard full-resolution particle filter-based tracker and a single wavelet subband (LL)(2)-based tracker, their multiscale tracker demonstrates significantly better tracking performance.

关键词： image fusion video signal processing image sequences object tracking particle filtering (numerical methods) set theory robust multiple object tracking adaptive subband particle filter fusion moving object tracking video sequences background motion shadows partial object camouflage low signal-to-noise ratio robust multiscale visual tracker captured video frame independent particle filters wavelet subband subset

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A proposed secure multiple watermarking technique based on DWT, DCT and SVD for application in medicine

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MULTIMEDIA TOOLS AND applications 2018年第4期77卷 4863-4882页

作者： Zear, Aditi Singh, Amit Kumar Kumar, Pardeep Jaypee Univ Informat Technol Waknaghat Dept Comp Sci & Engn Solan Himachal Prades India

In this paper, an algorithm for multiple watermarking based on discrete wavelet transforms (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) has been proposed for healthcare applications. For identity authentication purpose, the proposed method uses three watermarks in the form of medical Lump image watermark, the doctor signature/identification code and diagnostic information of the patient as the text watermarks. In order to improve the robustness performance of the image watermark, Back Propagation Neural Network (BPNN) is applied to the extracted image watermark to reduce the noise effects on the watermarked image. The security of the image watermark is also enhanced by using Arnold transform before embedding into the cover. Further, the symptom and signature text watermarks are also encoded by lossless arithmetic compression technique and Hamming error correction code respectively. The compressed and encoded text watermark is then embedded into the cover image. Experimental results are obtained by varying the gain factor, different sizes of text watermarks and the different cover image modalities. The results are provided to illustrate that the proposed method is able to withstand a different of signal processing attacks and has been found to be giving excellent performance for robustness, imperceptibility, capacity and security simultaneously. The robustness performance of the method is also compared with other reported techniques. Finally, the visual quality of the watermarked image is evaluated by the subjective method also. This shows that the visual quality of the watermarked images is acceptable for diagnosis at different gain factors. Therefore the proposed method may find potential application in prevention of patient identity theft in healthcare applications.

关键词： Multimedia data Discrete wavelet transforms Discrete cosine transform Singular value decomposition Back propagation neural network Healthcare

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A Blind Watermarking Technique using Redundant wavelet Transform for Copyright Protection 14

A Blind Watermarking Technique using Redundant Wavelet Trans...

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IEEE 14th International Colloquium on signal processing and its applications (CSPA)

作者： Ernawan, Ferda Kabir, Muhammad Nomani Univ Malaysia Pahang Fac Comp Syst & Software Engn Kuantan Malaysia

ISBN: (纸本)9781538603895

A digital watermarking technique is an alternative method to protect the intellectual property of digital images. This paper presents a hybrid blind watermarking technique formulated by combining RDWT with SVD considering a trade-off between imperceptibility and robustness. Watermark embedding locations are determined using a modified entropy of the host image. Watermark embedding is employed by examining the orthogonal matrix U obtained from the hybrid scheme RDWT-SVD. In the proposed scheme, the watermark image in binary format is scrambled by Arnold chaotic map to provide extra security. Our scheme is tested under different types of signal processing and geometrical attacks. The test results demonstrate that the proposed scheme provides higher robustness and less distortion than other existing schemes in withstanding JPEG2000 compression, cropping, scaling and other noises.

关键词： blind watermarking technique modified entropy watermark insertion watermark extraction redundant wavelet transform

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Generalized 2-Microlocal Frontier Prescription

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JOURNAL OF FOURIER ANALYSIS AND applications 2020年第6期26卷 88-88页

作者： Molter, Ursula Rosenblatt, Mariel Univ Buenos Aires FCEyN Dto Matemat Buenos Aires DF Argentina Univ Buenos Aires IMAS Buenos Aires DF Argentina Consejo Nacl Invest Cient & Tecn Buenos Aires DF Argentina Univ Nacl Gen Sarmiento IDH ICI Los Polvorines Buenos Aires Argentina

The characterization of local regularity is a fundamental issue in signal and image processing, since it contains relevant information about the underlying systems. The 2-microlocal frontier, a monotone concave downward curve in R-2, provides a useful way to classify pointwise singularity. In this paper we characterize all functions whose 2-microlocal frontier at a given point x(0) is a given line. Further, for a general concave downward curve, we obtain a large family of functions (or distributions) for which the 2-microlocal frontier is the given curve. This family contains-as special cases-the constructions given in Meyer (CRM monograph series, 1998), Guiheneuf et al. (ACHA 5(4):487-492, 1998) and Levy Vehel et al. (Proc Symp Pure Math 72:319-334, 2004). Moreover, following Levy Vehel et al. (2004), we extend our results to the prescription on a countable dense set.

关键词： 2-Microlocal analysis Pointwise regularity Regularity exponents wavelet analysis

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