Test and Evaluation of Teleconferencing Video Codecs Transmitting at 1.5 Mbps.

Science.gov (United States)

1985-08-01

video teleconferencing codecs on the market as of November 1984 to facilitate the choice of an appropriate frame format and data compression algorithm...Engineer, computer company, male 5. Chapter Officer, national civic organization, female Group Y: 6. Marketing Representative, communication systems...both mon:tors to C4ve t e evi uators an idea what kind of cictures they will have to ; ucge . Special suggestions were given regardinc the sequences witn

Temporal signal energy correction and low-complexity encoder feedback for lossy scalable video coding

NARCIS (Netherlands)

Loomans, M.J.H.; Koeleman, C.J.; With, de P.H.N.

2010-01-01

In this paper, we address two problems found in embedded implementations of Scalable Video Codecs (SVCs): the temporal signal energy distribution and frame-to-frame quality fluctuations. The unequal energy distribution between the low- and high-pass band with integer-based wavelets leads to

Codec-on-Demand Based on User-Level Virtualization

Science.gov (United States)

Zhang, Youhui; Zheng, Weimin

At work, at home, and in some public places, a desktop PC is usually available nowadays. Therefore, it is important for users to be able to play various videos on different PCs smoothly, but the diversity of codec types complicates the situation. Although some mainstream media players can try to download the needed codec automatically, this may fail for average users because installing the codec usually requires administrator privileges to complete, while the user may not be the owner of the PC. We believe an ideal solution should work without users' intervention, and need no special privileges. This paper proposes such a user-friendly, program-transparent solution for Windows-based media players. It runs the media player in a user-mode virtualization environment, and then downloads the needed codec on-the-fly. Because of API (Application Programming Interface) interception, some resource-accessing API calls from the player will be redirected to the downloaded codec resources. Then from the viewpoint of the player, the necessary codec exists locally and it can handle the video smoothly, although neither system registry nor system folders was modified during this process. Besides convenience, the principle of least privilege is maintained and the host system is left clean. This paper completely analyzes the technical issues and presents such a prototype which can work with DirectShow-compatible players. Performance tests show that the overhead is negligible. Moreover, our solution conforms to the Software-As-A-Service (SaaS) mode, which is very promising in the Internet era.

Parity Bit Replenishment for JPEG 2000-Based Video Streaming

Directory of Open Access Journals (Sweden)

François-Olivier Devaux

2009-01-01

Full Text Available This paper envisions coding with side information to design a highly scalable video codec. To achieve fine-grained scalability in terms of resolution, quality, and spatial access as well as temporal access to individual frames, the JPEG 2000 coding algorithm has been considered as the reference algorithm to encode INTRA information, and coding with side information has been envisioned to refresh the blocks that change between two consecutive images of a video sequence. One advantage of coding with side information compared to conventional closed-loop hybrid video coding schemes lies in the fact that parity bits are designed to correct stochastic errors and not to encode deterministic prediction errors. This enables the codec to support some desynchronization between the encoder and the decoder, which is particularly helpful to adapt on the fly pre-encoded content to fluctuating network resources and/or user preferences in terms of regions of interest. Regarding the coding scheme itself, to preserve both quality scalability and compliance to the JPEG 2000 wavelet representation, a particular attention has been devoted to the definition of a practical coding framework able to exploit not only the temporal but also spatial correlation among wavelet subbands coefficients, while computing the parity bits on subsets of wavelet bit-planes. Simulations have shown that compared to pure INTRA-based conditional replenishment solutions, the addition of the parity bits option decreases the transmission cost in terms of bandwidth, while preserving access flexibility.

High bit depth infrared image compression via low bit depth codecs

Science.gov (United States)

Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

2017-08-01

Future infrared remote sensing systems, such as monitoring of the Earth's environment by satellites, infrastructure inspection by unmanned airborne vehicles etc., will require 16 bit depth infrared images to be compressed and stored or transmitted for further analysis. Such systems are equipped with low power embedded platforms where image or video data is compressed by a hardware block called the video processing unit (VPU). However, in many cases using two 8-bit VPUs can provide advantages compared with using higher bit depth image compression directly. We propose to compress 16 bit depth images via 8 bit depth codecs in the following way. First, an input 16 bit depth image is mapped into 8 bit depth images, e.g., the first image contains only the most significant bytes (MSB image) and the second one contains only the least significant bytes (LSB image). Then each image is compressed by an image or video codec with 8 bits per pixel input format. We analyze how the compression parameters for both MSB and LSB images should be chosen to provide the maximum objective quality for a given compression ratio. Finally, we apply the proposed infrared image compression method utilizing JPEG and H.264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can achieve similar result as 16 bit HEVC codec.

Error Concealment for 3-D DWT Based Video Codec Using Iterative Thresholding

DEFF Research Database (Denmark)

Belyaev, Evgeny; Forchhammer, Søren; Codreanu, Marian

2017-01-01

Error concealment for video coding based on a 3-D discrete wavelet transform (DWT) is considered. We assume that the video sequence has a sparse representation in a known basis different from the DWT, e.g., in a 2-D discrete cosine transform basis. Then, we formulate the concealment problem as l1...

Wavelet-based audio embedding and audio/video compression

Science.gov (United States)

Mendenhall, Michael J.; Claypoole, Roger L., Jr.

2001-12-01

Watermarking, traditionally used for copyright protection, is used in a new and exciting way. An efficient wavelet-based watermarking technique embeds audio information into a video signal. Several effective compression techniques are applied to compress the resulting audio/video signal in an embedded fashion. This wavelet-based compression algorithm incorporates bit-plane coding, index coding, and Huffman coding. To demonstrate the potential of this audio embedding and audio/video compression algorithm, we embed an audio signal into a video signal and then compress. Results show that overall compression rates of 15:1 can be achieved. The video signal is reconstructed with a median PSNR of nearly 33 dB. Finally, the audio signal is extracted from the compressed audio/video signal without error.

Quality Variation Control for Three-Dimensional Wavelet-Based Video Coders

Directory of Open Access Journals (Sweden)

Vidhya Seran

2007-02-01

Full Text Available The fluctuation of quality in time is a problem that exists in motion-compensated-temporal-filtering (MCTF- based video coding. The goal of this paper is to design a solution for overcoming the distortion fluctuation challenges faced by wavelet-based video coders. We propose a new technique for determining the number of bits to be allocated to each temporal subband in order to minimize the fluctuation in the quality of the reconstructed video. Also, the wavelet filter properties are explored to design suitable scaling coefficients with the objective of smoothening the temporal PSNR. The biorthogonal 5/3 wavelet filter is considered in this paper and experimental results are presented for 2D+t and t+2D MCTF wavelet coders.

Quality Variation Control for Three-Dimensional Wavelet-Based Video Coders

Directory of Open Access Journals (Sweden)

Seran Vidhya

2007-01-01

Full Text Available The fluctuation of quality in time is a problem that exists in motion-compensated-temporal-filtering (MCTF- based video coding. The goal of this paper is to design a solution for overcoming the distortion fluctuation challenges faced by wavelet-based video coders. We propose a new technique for determining the number of bits to be allocated to each temporal subband in order to minimize the fluctuation in the quality of the reconstructed video. Also, the wavelet filter properties are explored to design suitable scaling coefficients with the objective of smoothening the temporal PSNR. The biorthogonal 5/3 wavelet filter is considered in this paper and experimental results are presented for 2D+t and t+2D MCTF wavelet coders.

A hybrid video compression based on zerotree wavelet structure

International Nuclear Information System (INIS)

Kilic, Ilker; Yilmaz, Reyat

2009-01-01

A video compression algorithm comparable to the standard techniques at low bit rates is presented in this paper. The overlapping block motion compensation (OBMC) is combined with discrete wavelet transform which followed by Lloyd-Max quantization and zerotree wavelet (ZTW) structure. The novel feature of this coding scheme is the combination of hierarchical finite state vector quantization (HFSVQ) with the ZTW to encode the quantized wavelet coefficients. It is seen that the proposed video encoder (ZTW-HFSVQ) performs better than the MPEG-4 and Zerotree Entropy Coding (ZTE). (author)

Codecs

Science.gov (United States)

Britton, Eliot

This thesis contains two volumes. The first is a written text that describes my compositional techniques in the context of an analysis of Codecs. The second volume is the score of this work. Volume one is divided into six sections: Introduction, harmony, rhythm and time, melodic materials, form, live electronics and future directions. Each section describes techniques and processes I developed throughout the compositional process. Codecs was inspired by the subversive proliferation musical materials though the use of audio codecs. I developed compositional tools based on encryption and compression in order to explore the audio codec metaphor. Volume two is the full score of Codecs, a work for large ensemble and live electronics. It is comprised of three sections and has a duration of approximately 14 minutes. The work is scored for flute (doubling on piccolo), oboe, clarinet in Bb (doubling on bass clarinet), bassoon, horn in F, trumpet, trombone, tuba, string quintet and percussion. Electronic drum pads and captured live sounds are used to control the live electronic elements.

Digital Signal Processing For Low Bit Rate TV Image Codecs

Science.gov (United States)

Rao, K. R.

1987-06-01

In view of the 56 KBPS digital switched network services and the ISDN, low bit rate codecs for providing real time full motion color video are under various stages of development. Some companies have already brought the codecs into the market. They are being used by industry and some Federal Agencies for video teleconferencing. In general, these codecs have various features such as multiplexing audio and data, high resolution graphics, encryption, error detection and correction, self diagnostics, freezeframe, split video, text overlay etc. To transmit the original color video on a 56 KBPS network requires bit rate reduction of the order of 1400:1. Such a large scale bandwidth compression can be realized only by implementing a number of sophisticated,digital signal processing techniques. This paper provides an overview of such techniques and outlines the newer concepts that are being investigated. Before resorting to the data compression techniques, various preprocessing operations such as noise filtering, composite-component transformation and horizontal and vertical blanking interval removal are to be implemented. Invariably spatio-temporal subsampling is achieved by appropriate filtering. Transform and/or prediction coupled with motion estimation and strengthened by adaptive features are some of the tools in the arsenal of the data reduction methods. Other essential blocks in the system are quantizer, bit allocation, buffer, multiplexer, channel coding etc.

Image compression with Iris-C

Science.gov (United States)

Gains, David

2009-05-01

Iris-C is an image codec designed for streaming video applications that demand low bit rate, low latency, lossless image compression. To achieve compression and low latency the codec features the discrete wavelet transform, Exp-Golomb coding, and online processes that construct dynamic models of the input video. Like H.264 and Dirac, the Iris-C codec accepts input video from both the YUV and YCOCG colour spaces, but the system can also operate on Bayer RAW data read directly from an image sensor. Testing shows that the Iris-C codec is competitive with the Dirac low delay syntax codec which is typically regarded as the state-of-the-art low latency, lossless video compressor.

3D Scan-Based Wavelet Transform and Quality Control for Video Coding

Directory of Open Access Journals (Sweden)

Parisot Christophe

2003-01-01

Full Text Available Wavelet coding has been shown to achieve better compression than DCT coding and moreover allows scalability. 2D DWT can be easily extended to 3D and thus applied to video coding. However, 3D subband coding of video suffers from two drawbacks. The first is the amount of memory required for coding large 3D blocks; the second is the lack of temporal quality due to the sequence temporal splitting. In fact, 3D block-based video coders produce jerks. They appear at blocks temporal borders during video playback. In this paper, we propose a new temporal scan-based wavelet transform method for video coding combining the advantages of wavelet coding (performance, scalability with acceptable reduced memory requirements, no additional CPU complexity, and avoiding jerks. We also propose an efficient quality allocation procedure to ensure a constant quality over time.

A CABAC codec of H.264AVC with secure arithmetic coding

Science.gov (United States)

Neji, Nihel; Jridi, Maher; Alfalou, Ayman; Masmoudi, Nouri

2013-02-01

This paper presents an optimized H.264/AVC coding system for HDTV displays based on a typical flow with high coding efficiency and statics adaptivity features. For high quality streaming, the codec uses a Binary Arithmetic Encoding/Decoding algorithm with high complexity and a JVCE (Joint Video compression and encryption) scheme. In fact, particular attention is given to simultaneous compression and encryption applications to gain security without compromising the speed of transactions [1]. The proposed design allows us to encrypt the information using a pseudo-random number generator (PRNG). Thus we achieved the two operations (compression and encryption) simultaneously and in a dependent manner which is a novelty in this kind of architecture. Moreover, we investigated the hardware implementation of CABAC (Context-based adaptive Binary Arithmetic Coding) codec. The proposed architecture is based on optimized binarizer/de-binarizer to handle significant pixel rates videos with low cost and high performance for most frequent SEs. This was checked using HD video frames. The obtained synthesis results using an FPGA (Xilinx's ISE) show that our design is relevant to code main profile video stream.

High Definition Video Streaming Using H.264 Video Compression

OpenAIRE

Bechqito, Yassine

2009-01-01

This thesis presents high definition video streaming using H.264 codec implementation. The experiment carried out in this study was done for an offline streaming video but a model for live high definition streaming is introduced, as well. Prior to the actual experiment, this study describes digital media streaming. Also, the different technologies involved in video streaming are covered. These include streaming architecture and a brief overview on H.264 codec as well as high definition t...

JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

Directory of Open Access Journals (Sweden)

Thomas André

2007-03-01

Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

Directory of Open Access Journals (Sweden)

André Thomas

2007-01-01

Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

Wavelet packet transform-based robust video watermarking technique

Indian Academy of Sciences (India)

If any conflict happens to the copyright identification and authentication, ... the present work is concentrated on the robust digital video watermarking. .... the wavelet decomposition, resulting in a new family of orthonormal bases for function ...

Design considerations for computationally constrained two-way real-time video communication

Science.gov (United States)

Bivolarski, Lazar M.; Saunders, Steven E.; Ralston, John D.

2009-08-01

Today's video codecs have evolved primarily to meet the requirements of the motion picture and broadcast industries, where high-complexity studio encoding can be utilized to create highly-compressed master copies that are then broadcast one-way for playback using less-expensive, lower-complexity consumer devices for decoding and playback. Related standards activities have largely ignored the computational complexity and bandwidth constraints of wireless or Internet based real-time video communications using devices such as cell phones or webcams. Telecommunications industry efforts to develop and standardize video codecs for applications such as video telephony and video conferencing have not yielded image size, quality, and frame-rate performance that match today's consumer expectations and market requirements for Internet and mobile video services. This paper reviews the constraints and the corresponding video codec requirements imposed by real-time, 2-way mobile video applications. Several promising elements of a new mobile video codec architecture are identified, and more comprehensive computational complexity metrics and video quality metrics are proposed in order to support the design, testing, and standardization of these new mobile video codecs.

A clinical distortion index for compressed echocardiogram evaluation: recommendations for Xvid codec

International Nuclear Information System (INIS)

Alesanco, A; Hernández, C; García, J; Portolés, A; Aured, C; García, M; Ramos, L; Serrano, P

2009-01-01

This paper introduces a new clinical distortion index able to measure the decrease in diagnostic content in compressed echocardiograms. It is calculated using cardiologists' answers to a clinical testbed composed of two types of tests: one blind and the other semi-blind. This index may be used to compare clinical performance among video codecs from a clinical perspective. It can also be used to classify compression rates into useful and useless ranges, thus providing recommendations for echocardiogram compression. A study carried out in order to illustrate its use with Xvid video codec is also presented. The results obtained showed that, for 2D and M modes, the transmission rate should be at least 768 kbit s −1 and for color Doppler mode and pulsed/continuous Doppler, 256 kbit s −1

KOMPRESI CITRA MEDIS MENGGUNAKAN PACKET WAVELET TRANSFORM DAN RUN LENGTH ENCODING

Directory of Open Access Journals (Sweden)

I Made Ari Dwi Suta Atmaja

2018-03-01

Full Text Available Citra medis memegang peranan yang sangat penting dalam dunia medis saat ini. Biasanya citra medis membutuhkan penyimpanan yang cukup besar pada komputer. Penelitian ini bertujuan untuk melakukan kompresi pada citra medis menggunakan wavelet packet transform (PWT dan run length encoding (RLE. Tiga jenis codec yaitu Haar, Daubechies dan Biorthogonal digunakan dalam penelitian ini. Penelitian ini membandingkan rasio kompresi, waktu kompresi dan dekompresi untuk setiap citra. Penelitian ini menggunakan tiga nilai threshold yaitu 30, 40 dan 50. Percobaan yang dilakukan menggunakan lima citra medis yang mewakili jenis citra hasil X-ray, USG dan CT-Scan sebagai data testing. Penelitian ini menunjukkan bahwa codec Haar dan Biorthogonal memberikan hasil yang lebih baik dibandingkan codec Daubechies dalam hal kualitas citra (PSNR dan rasio. Akan tetapi untuk waktu kompresi, codec Daubechies lebih cepat meskipun tidak secara signifikan.

Efficient random access high resolution region-of-interest (ROI) image retrieval using backward coding of wavelet trees (BCWT)

Science.gov (United States)

Corona, Enrique; Nutter, Brian; Mitra, Sunanda; Guo, Jiangling; Karp, Tanja

2008-03-01

Efficient retrieval of high quality Regions-Of-Interest (ROI) from high resolution medical images is essential for reliable interpretation and accurate diagnosis. Random access to high quality ROI from codestreams is becoming an essential feature in many still image compression applications, particularly in viewing diseased areas from large medical images. This feature is easier to implement in block based codecs because of the inherent spatial independency of the code blocks. This independency implies that the decoding order of the blocks is unimportant as long as the position for each is properly identified. In contrast, wavelet-tree based codecs naturally use some interdependency that exploits the decaying spectrum model of the wavelet coefficients. Thus one must keep track of the decoding order from level to level with such codecs. We have developed an innovative multi-rate image subband coding scheme using "Backward Coding of Wavelet Trees (BCWT)" which is fast, memory efficient, and resolution scalable. It offers far less complexity than many other existing codecs including both, wavelet-tree, and block based algorithms. The ROI feature in BCWT is implemented through a transcoder stage that generates a new BCWT codestream containing only the information associated with the user-defined ROI. This paper presents an efficient technique that locates a particular ROI within the BCWT coded domain, and decodes it back to the spatial domain. This technique allows better access and proper identification of pathologies in high resolution images since only a small fraction of the codestream is required to be transmitted and analyzed.

On the definition of adapted audio/video profiles for high-quality video calling services over LTE/4G

Science.gov (United States)

Ndiaye, Maty; Quinquis, Catherine; Larabi, Mohamed Chaker; Le Lay, Gwenael; Saadane, Hakim; Perrine, Clency

2014-01-01

During the last decade, the important advances and widespread availability of mobile technology (operating systems, GPUs, terminal resolution and so on) have encouraged a fast development of voice and video services like video-calling. While multimedia services have largely grown on mobile devices, the generated increase of data consumption is leading to the saturation of mobile networks. In order to provide data with high bit-rates and maintain performance as close as possible to traditional networks, the 3GPP (The 3rd Generation Partnership Project) worked on a high performance standard for mobile called Long Term Evolution (LTE). In this paper, we aim at expressing recommendations related to audio and video media profiles (selection of audio and video codecs, bit-rates, frame-rates, audio and video formats) for a typical video-calling services held over LTE/4G mobile networks. These profiles are defined according to targeted devices (smartphones, tablets), so as to ensure the best possible quality of experience (QoE). Obtained results indicate that for a CIF format (352 x 288 pixels) which is usually used for smartphones, the VP8 codec provides a better image quality than the H.264 codec for low bitrates (from 128 to 384 kbps). However sequences with high motion, H.264 in slow mode is preferred. Regarding audio, better results are globally achieved using wideband codecs offering good quality except for opus codec (at 12.2 kbps).

Error Resilience in Current Distributed Video Coding Architectures

Directory of Open Access Journals (Sweden)

Tonoli Claudia

2009-01-01

Full Text Available In distributed video coding the signal prediction is shifted at the decoder side, giving therefore most of the computational complexity burden at the receiver. Moreover, since no prediction loop exists before transmission, an intrinsic robustness to transmission errors has been claimed. This work evaluates and compares the error resilience performance of two distributed video coding architectures. In particular, we have considered a video codec based on the Stanford architecture (DISCOVER codec and a video codec based on the PRISM architecture. Specifically, an accurate temporal and rate/distortion based evaluation of the effects of the transmission errors for both the considered DVC architectures has been performed and discussed. These approaches have been also compared with H.264/AVC, in both cases of no error protection, and simple FEC error protection. Our evaluations have highlighted in all cases a strong dependence of the behavior of the various codecs to the content of the considered video sequence. In particular, PRISM seems to be particularly well suited for low-motion sequences, whereas DISCOVER provides better performance in the other cases.

Accelerating wavelet-based video coding on graphics hardware using CUDA

NARCIS (Netherlands)

Laan, van der W.J.; Roerdink, J.B.T.M.; Jalba, A.C.; Zinterhof, P.; Loncaric, S.; Uhl, A.; Carini, A.

2009-01-01

The DiscreteWavelet Transform (DWT) has a wide range of applications from signal processing to video and image compression. This transform, by means of the lifting scheme, can be performed in a memory and computation efficient way on modern, programmable GPUs, which can be regarded as massively

Accelerating Wavelet-Based Video Coding on Graphics Hardware using CUDA

NARCIS (Netherlands)

Laan, Wladimir J. van der; Roerdink, Jos B.T.M.; Jalba, Andrei C.; Zinterhof, P; Loncaric, S; Uhl, A; Carini, A

2009-01-01

The Discrete Wavelet Transform (DWT) has a wide range of applications from signal processing to video and image compression. This transform, by means of the lifting scheme, can be performed in a memory mid computation efficient way on modern, programmable GPUs, which can be regarded as massively

A No-Reference Modular Video Quality Prediction Model for H.265/HEVC and VP9 Codecs on a Mobile Device

Directory of Open Access Journals (Sweden)

Debajyoti Pal

2017-01-01

Full Text Available We propose a modular no-reference video quality prediction model for videos that are encoded with H.265/HEVC and VP9 codecs and viewed on mobile devices. The impairments which can affect video transmission are classified into two broad types depending upon which layer of the TCP/IP model they originated from. Impairments from the network layer are called the network QoS factors, while those from the application layer are called the application/payload QoS factors. Initially we treat the network and application QoS factors separately and find out the 1 : 1 relationship between the respective QoS factors and the corresponding perceived video quality or QoE. The mapping from the QoS to the QoE domain is based upon a decision variable that gives an optimal performance. Next, across each group we choose multiple QoS factors and find out the QoE for such multifactor impaired videos by using an additive, multiplicative, and regressive approach. We refer to these as the integrated network and application QoE, respectively. At the end, we use a multiple regression approach to combine the network and application QoE for building the final model. We also use an Artificial Neural Network approach for building the model and compare its performance with the regressive approach.

ANALISIS LAYANAN VOIP PADA JARINGAN MANET DENGAN CODEC YANG BERBEDA

Directory of Open Access Journals (Sweden)

Randa Oktavada Zein

2016-12-01

Full Text Available Voice Over Internet Protocol (VoIP merupakan layanan bersifat real-time, parameter yang dapat mempengaruhi kulitas layanan seperti delay, jitter dan packet loss. Dalam proses pengkodean sinyal analog menjadi sinyal digital menyebabkan terjadiya delay pada VoIP. Sistem pengcodean ini disebut codec, setiap codec memiliki bitrate yang berbeda pengkodeannya. Pada penelitian ini menggunakan codec G.711, G729 dan codec G.723.1 sebagai perbandingan untuk mengetahui qulity of service (QoS VoIP jika diterapkan pada jaringan MANET. Dengan penambahan aplikasi Hypertext Transfer Protovol (HTTP untuk mendapatkan parameter QoS VoIP dari codec G.711, G.729 dan G.723.1. Hasil yang didapat pada codec G.723.1 lebih baik jika dibandingkan dengan codec g.711 dan G.729 dilihat dari nilai dari parameter QoS seperti delay, jitter dan packet loss. Sesuai standar ITU-T G114 dimana perhitunan teoritis parameter dari codec G.723.1 didapat hasil terendah 7,68 kbps.

Video coding standards AVS China, H.264/MPEG-4 PART 10, HEVC, VP6, DIRAC and VC-1

CERN Document Server

Rao, K R; Hwang, Jae Jeong

2014-01-01

Review by Ashraf A. Kassim, Professor, Department of Electrical & Computer Engineering, and Associate Dean, School of Engineering, National University of Singapore.     The book consists of eight chapters of which the first two provide an overview of various video & image coding standards, and video formats. The next four chapters present in detail the Audio & video standard (AVS) of China, the H.264/MPEG-4 Advanced video coding (AVC) standard, High efficiency video coding (HEVC) standard and the VP6 video coding standard (now VP10) respectively. The performance of the wavelet based Dirac video codec is compared with H.264/MPEG-4 AVC in chapter 7. Finally in chapter 8, the VC-1 video coding standard is presented together with VC-2 which is based on the intra frame coding of Dirac and an outline of a H.264/AVC to VC-1 transcoder.   The authors also present and discuss relevant research literature such as those which document improved methods & techniques, and also point to other related reso...

Basic prediction techniques in modern video coding standards

CERN Document Server

Kim, Byung-Gyu

2016-01-01

This book discusses in detail the basic algorithms of video compression that are widely used in modern video codec. The authors dissect complicated specifications and present material in a way that gets readers quickly up to speed by describing video compression algorithms succinctly, without going to the mathematical details and technical specifications. For accelerated learning, hybrid codec structure, inter- and intra- prediction techniques in MPEG-4, H.264/AVC, and HEVC are discussed together. In addition, the latest research in the fast encoder design for the HEVC and H.264/AVC is also included.

An adaptive mode-driven spatiotemporal motion vector prediction for wavelet video coding

Science.gov (United States)

Zhao, Fan; Liu, Guizhong; Qi, Yong

2010-07-01

The three-dimensional subband/wavelet codecs use 5/3 filters rather than Haar filters for the motion compensation temporal filtering (MCTF) to improve the coding gain. In order to curb the increased motion vector rate, an adaptive motion mode driven spatiotemporal motion vector prediction (AMDST-MVP) scheme is proposed. First, by making use of the direction histograms of four motion vector fields resulting from the initial spatial motion vector prediction (SMVP), the motion mode of the current GOP is determined according to whether the fast or complex motion exists in the current GOP. Then the GOP-level MVP scheme is thereby determined by either the S-MVP or the AMDST-MVP, namely, AMDST-MVP is the combination of S-MVP and temporal-MVP (T-MVP). If the latter is adopted, the motion vector difference (MVD) between the neighboring MV fields and the S-MVP resulting MV of the current block is employed to decide whether or not the MV of co-located block in the previous frame is used for prediction the current block. Experimental results show that AMDST-MVP not only can improve the coding efficiency but also reduce the number of computation complexity.

Mutiple LDPC Decoding using Bitplane Correlation for Transform Domain Wyner-Ziv Video Coding

DEFF Research Database (Denmark)

Luong, Huynh Van; Huang, Xin; Forchhammer, Søren

2011-01-01

Distributed video coding (DVC) is an emerging video coding paradigm for systems which fully or partly exploit the source statistics at the decoder to reduce the computational burden at the encoder. This paper considers a Low Density Parity Check (LDPC) based Transform Domain Wyner-Ziv (TDWZ) video...... codec. To improve the LDPC coding performance in the context of TDWZ, this paper proposes a Wyner-Ziv video codec using bitplane correlation through multiple parallel LDPC decoding. The proposed scheme utilizes inter bitplane correlation to enhance the bitplane decoding performance. Experimental results...

Scalable-to-lossless transform domain distributed video coding

DEFF Research Database (Denmark)

Huang, Xin; Ukhanova, Ann; Veselov, Anton

2010-01-01

Distributed video coding (DVC) is a novel approach providing new features as low complexity encoding by mainly exploiting the source statistics at the decoder based on the availability of decoder side information. In this paper, scalable-tolossless DVC is presented based on extending a lossy Tran...... codec provides frame by frame encoding. Comparing the lossless coding efficiency, the proposed scalable-to-lossless TDWZ video codec can save up to 5%-13% bits compared to JPEG LS and H.264 Intra frame lossless coding and do so as a scalable-to-lossless coding....

Embedded DCT and wavelet methods for fine granular scalable video: analysis and comparison

Science.gov (United States)

van der Schaar-Mitrea, Mihaela; Chen, Yingwei; Radha, Hayder

2000-04-01

Video transmission over bandwidth-varying networks is becoming increasingly important due to emerging applications such as streaming of video over the Internet. The fundamental obstacle in designing such systems resides in the varying characteristics of the Internet (i.e. bandwidth variations and packet-loss patterns). In MPEG-4, a new SNR scalability scheme, called Fine-Granular-Scalability (FGS), is currently under standardization, which is able to adapt in real-time (i.e. at transmission time) to Internet bandwidth variations. The FGS framework consists of a non-scalable motion-predicted base-layer and an intra-coded fine-granular scalable enhancement layer. For example, the base layer can be coded using a DCT-based MPEG-4 compliant, highly efficient video compression scheme. Subsequently, the difference between the original and decoded base-layer is computed, and the resulting FGS-residual signal is intra-frame coded with an embedded scalable coder. In order to achieve high coding efficiency when compressing the FGS enhancement layer, it is crucial to analyze the nature and characteristics of residual signals common to the SNR scalability framework (including FGS). In this paper, we present a thorough analysis of SNR residual signals by evaluating its statistical properties, compaction efficiency and frequency characteristics. The signal analysis revealed that the energy compaction of the DCT and wavelet transforms is limited and the frequency characteristic of SNR residual signals decay rather slowly. Moreover, the blockiness artifacts of the low bit-rate coded base-layer result in artificial high frequencies in the residual signal. Subsequently, a variety of wavelet and embedded DCT coding techniques applicable to the FGS framework are evaluated and their results are interpreted based on the identified signal properties. As expected from the theoretical signal analysis, the rate-distortion performances of the embedded wavelet and DCT-based coders are very

Holovideo: Real-time 3D range video encoding and decoding on GPU

Science.gov (United States)

Karpinsky, Nikolaus; Zhang, Song

2012-02-01

We present a 3D video-encoding technique called Holovideo that is capable of encoding high-resolution 3D videos into standard 2D videos, and then decoding the 2D videos back into 3D rapidly without significant loss of quality. Due to the nature of the algorithm, 2D video compression such as JPEG encoding with QuickTime Run Length Encoding (QTRLE) can be applied with little quality loss, resulting in an effective way to store 3D video at very small file sizes. We found that under a compression ratio of 134:1, Holovideo to OBJ file format, the 3D geometry quality drops at a negligible level. Several sets of 3D videos were captured using a structured light scanner, compressed using the Holovideo codec, and then uncompressed and displayed to demonstrate the effectiveness of the codec. With the use of OpenGL Shaders (GLSL), the 3D video codec can encode and decode in realtime. We demonstrated that for a video size of 512×512, the decoding speed is 28 frames per second (FPS) with a laptop computer using an embedded NVIDIA GeForce 9400 m graphics processing unit (GPU). Encoding can be done with this same setup at 18 FPS, making this technology suitable for applications such as interactive 3D video games and 3D video conferencing.

Data Partitioning Technique for Improved Video Prioritization

Directory of Open Access Journals (Sweden)

Ismail Amin Ali

2017-07-01

Full Text Available A compressed video bitstream can be partitioned according to the coding priority of the data, allowing prioritized wireless communication or selective dropping in a congested channel. Known as data partitioning in the H.264/Advanced Video Coding (AVC codec, this paper introduces a further sub-partition of one of the H.264/AVC codec’s three data-partitions. Results show a 5 dB improvement in Peak Signal-to-Noise Ratio (PSNR through this innovation. In particular, the data partition containing intra-coded residuals is sub-divided into data from: those macroblocks (MBs naturally intra-coded, and those MBs forcibly inserted for non-periodic intra-refresh. Interactive user-to-user video streaming can benefit, as then HTTP adaptive streaming is inappropriate and the High Efficiency Video Coding (HEVC codec is too energy demanding.

High bit depth infrared image compression via low bit depth codecs

DEFF Research Database (Denmark)

Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

.264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can...

Impact of Constant Rate Factor on Objective Video Quality Assessment

Directory of Open Access Journals (Sweden)

Juraj Bienik

2017-01-01

Full Text Available This paper deals with the impact of constant rate factor value on the objective video quality assessment using PSNR and SSIM metrics. Compression efficiency of H.264 and H.265 codecs defined by different Constant rate factor (CRF values was tested. The assessment was done for eight types of video sequences depending on content for High Definition (HD, Full HD (FHD and Ultra HD (UHD resolution. Finally, performance of both mentioned codecs with emphasis on compression ratio and efficiency of coding was compared.

Encoder power consumption comparison of Distributed Video Codec and H.264/AVC in low-complexity mode

DEFF Research Database (Denmark)

Ukhanova, Ann; Belyaev, Evgeny; Forchhammer, Søren

2010-01-01

(ME) and CABAC entropy coder consume much power so we eliminate ME from the codec and use CAVLC instead of CABAC. Some investigations show that low-complexity DVC outperforms other algorithms in terms of encoder side energy consumption . However, estimations of power consumption for H.264/AVC and DVC...

QIM blind video watermarking scheme based on Wavelet transform and principal component analysis

Directory of Open Access Journals (Sweden)

Nisreen I. Yassin

2014-12-01

Full Text Available In this paper, a blind scheme for digital video watermarking is proposed. The security of the scheme is established by using one secret key in the retrieval of the watermark. Discrete Wavelet Transform (DWT is applied on each video frame decomposing it into a number of sub-bands. Maximum entropy blocks are selected and transformed using Principal Component Analysis (PCA. Quantization Index Modulation (QIM is used to quantize the maximum coefficient of the PCA blocks of each sub-band. Then, the watermark is embedded into the selected suitable quantizer values. The proposed scheme is tested using a number of video sequences. Experimental results show high imperceptibility. The computed average PSNR exceeds 45 dB. Finally, the scheme is applied on two medical videos. The proposed scheme shows high robustness against several attacks such as JPEG coding, Gaussian noise addition, histogram equalization, gamma correction, and contrast adjustment in both cases of regular videos and medical videos.

Exploring inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video

Science.gov (United States)

Li, Jia; Tian, Yonghong; Gao, Wen

2008-01-01

In recent years, the amount of streaming video has grown rapidly on the Web. Often, retrieving these streaming videos offers the challenge of indexing and analyzing the media in real time because the streams must be treated as effectively infinite in length, thus precluding offline processing. Generally speaking, captions are important semantic clues for video indexing and retrieval. However, existing caption detection methods often have difficulties to make real-time detection for streaming video, and few of them concern on the differentiation of captions from scene texts and scrolling texts. In general, these texts have different roles in streaming video retrieval. To overcome these difficulties, this paper proposes a novel approach which explores the inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video. In our approach, the inter-frame correlation information is used to distinguish caption texts from scene texts and scrolling texts. Moreover, wavelet-domain Generalized Gaussian Models (GGMs) are utilized to automatically remove non-text regions from each frame and only keep caption regions for further processing. Experiment results show that our approach is able to offer real-time caption detection with high recall and low false alarm rate, and also can effectively discern caption texts from the other texts even in low resolutions.

High bit depth infrared image compression via low bit depth codecs

DEFF Research Database (Denmark)

Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

2017-01-01

images via 8 bit depth codecs in the following way. First, an input 16 bit depth image is mapped into 8 bit depth images, e.g., the first image contains only the most significant bytes (MSB image) and the second one contains only the least significant bytes (LSB image). Then each image is compressed.......264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can...

No-Reference Video Quality Assessment using Codec Analysis

DEFF Research Database (Denmark)

Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

2015-01-01

types of videos, estimating the level of quantization used in the I-frames, and exploiting this information to assess the video quality. In order to do this for H.264/AVC, the distribution of the DCT-coefficients after intra-prediction and deblocking are modeled. To obtain VQA features for H.264/AVC, we......A no-reference video quality assessment (VQA) method is presented for videos distorted by H.264/AVC and MPEG-2. The assessment is performed without access to the bit-stream. Instead we analyze and estimate coefficients based on decoded pixels. The approach involves distinguishing between the two...... propose a novel estimation method of the quantization in H.264/AVC videos without bitstream access, which can also be used for Peak Signalto-Noise Ratio (PSNR) estimation. The results from the MPEG-2 and H.264/AVC analysis are mapped to a perceptual measure of video quality by Support Vector Regression...

An improvement analysis on video compression using file segmentation

Science.gov (United States)

Sharma, Shubhankar; Singh, K. John; Priya, M.

2017-11-01

From the past two decades the extreme evolution of the Internet has lead a massive rise in video technology and significantly video consumption over the Internet which inhabits the bulk of data traffic in general. Clearly, video consumes that so much data size on the World Wide Web, to reduce the burden on the Internet and deduction of bandwidth consume by video so that the user can easily access the video data.For this, many video codecs are developed such as HEVC/H.265 and V9. Although after seeing codec like this one gets a dilemma of which would be improved technology in the manner of rate distortion and the coding standard.This paper gives a solution about the difficulty for getting low delay in video compression and video application e.g. ad-hoc video conferencing/streaming or observation by surveillance. Also this paper describes the benchmark of HEVC and V9 technique of video compression on subjective oral estimations of High Definition video content, playback on web browsers. Moreover, this gives the experimental ideology of dividing the video file into several segments for compression and putting back together to improve the efficiency of video compression on the web as well as on the offline mode.

Toward enhancing the distributed video coder under a multiview video codec framework

Science.gov (United States)

Lee, Shih-Chieh; Chen, Jiann-Jone; Tsai, Yao-Hong; Chen, Chin-Hua

2016-11-01

The advance of video coding technology enables multiview video (MVV) or three-dimensional television (3-D TV) display for users with or without glasses. For mobile devices or wireless applications, a distributed video coder (DVC) can be utilized to shift the encoder complexity to decoder under the MVV coding framework, denoted as multiview distributed video coding (MDVC). We proposed to exploit both inter- and intraview video correlations to enhance side information (SI) and improve the MDVC performance: (1) based on the multiview motion estimation (MVME) framework, a categorized block matching prediction with fidelity weights (COMPETE) was proposed to yield a high quality SI frame for better DVC reconstructed images. (2) The block transform coefficient properties, i.e., DCs and ACs, were exploited to design the priority rate control for the turbo code, such that the DVC decoding can be carried out with fewest parity bits. In comparison, the proposed COMPETE method demonstrated lower time complexity, while presenting better reconstructed video quality. Simulations show that the proposed COMPETE can reduce the time complexity of MVME to 1.29 to 2.56 times smaller, as compared to previous hybrid MVME methods, while the image peak signal to noise ratios (PSNRs) of a decoded video can be improved 0.2 to 3.5 dB, as compared to H.264/AVC intracoding.

Joint disparity and motion estimation using optical flow for multiview Distributed Video Coding

DEFF Research Database (Denmark)

Salmistraro, Matteo; Raket, Lars Lau; Brites, Catarina

2014-01-01

Distributed Video Coding (DVC) is a video coding paradigm where the source statistics are exploited at the decoder based on the availability of Side Information (SI). In a monoview video codec, the SI is generated by exploiting the temporal redundancy of the video, through motion estimation and c...

No-Reference Video Quality Assessment by HEVC Codec Analysis

DEFF Research Database (Denmark)

Huang, Xin; Søgaard, Jacob; Forchhammer, Søren

2015-01-01

This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by High Efficiency Video Coding (HEVC). The proposed assessment can be performed either as a BitstreamBased (BB) method or as a Pixel-Based (PB). It extracts or estimates...... the transform coefficients, estimates the distortion, and assesses the video quality. The proposed scheme generates VQA features based on Intra coded frames, and then maps features using an Elastic Net to predict subjective video quality. A set of HEVC coded 4K UHD sequences are tested. Results show...... that the quality scores computed by the proposed method are highly correlated with the subjective assessment....

Wavelet based mobile video watermarking: spread spectrum vs. informed embedding

Science.gov (United States)

Mitrea, M.; Prêteux, F.; Duţă, S.; Petrescu, M.

2005-11-01

The cell phone expansion provides an additional direction for digital video content distribution: music clips, news, sport events are more and more transmitted toward mobile users. Consequently, from the watermarking point of view, a new challenge should be taken: very low bitrate contents (e.g. as low as 64 kbit/s) are now to be protected. Within this framework, the paper approaches for the first time the mathematical models for two random processes, namely the original video to be protected and a very harmful attack any watermarking method should face the StirMark attack. By applying an advanced statistical investigation (combining the Chi square, Ro, Fisher and Student tests) in the discrete wavelet domain, it is established that the popular Gaussian assumption can be very restrictively used when describing the former process and has nothing to do with the latter. As these results can a priori determine the performances of several watermarking methods, both of spread spectrum and informed embedding types, they should be considered in the design stage.

Content Adaptive Lagrange Multiplier Selection for Rate-Distortion Optimization in 3-D Wavelet-Based Scalable Video Coding

Directory of Open Access Journals (Sweden)

Ying Chen

2018-03-01

Full Text Available Rate-distortion optimization (RDO plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC. Among all the possible coding modes, it aims to select the one which has the best trade-off between bitrate and compression distortion. Specifically, this tradeoff is tuned through the choice of the Lagrange multiplier. Despite the prevalence of conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to 3-D wavelet-based SVC where the explicit values of the quantization step are not available, with on consideration of the content features of input signal. In this paper, an efficient content adaptive Lagrange multiplier selection algorithm is proposed in the context of RDO for 3-D wavelet-based SVC targeting quality scalability. Our contributions are two-fold. First, we introduce a novel weighting method, which takes account of the mutual information, gradient per pixel, and texture homogeneity to measure the temporal subband characteristics after applying the motion-compensated temporal filtering (MCTF technique. Second, based on the proposed subband weighting factor model, we derive the optimal Lagrange multiplier. Experimental results demonstrate that the proposed algorithm enables more satisfactory video quality with negligible additional computational complexity.

Adaptive Noise Model for Transform Domain Wyner-Ziv Video using Clustering of DCT Blocks

DEFF Research Database (Denmark)

Luong, Huynh Van; Huang, Xin; Forchhammer, Søren

2011-01-01

The noise model is one of the most important aspects influencing the coding performance of Distributed Video Coding. This paper proposes a novel noise model for Transform Domain Wyner-Ziv (TDWZ) video coding by using clustering of DCT blocks. The clustering algorithm takes advantage of the residual...... modelling. Furthermore, the proposed cluster level noise model is adaptively combined with a coefficient level noise model in this paper to robustly improve coding performance of TDWZ video codec up to 1.24 dB (by Bjøntegaard metric) compared to the DISCOVER TDWZ video codec....... information of all frequency bands, iteratively classifies blocks into different categories and estimates the noise parameter in each category. The experimental results show that the coding performance of the proposed cluster level noise model is competitive with state-ofthe- art coefficient level noise...

Wavelet library for constrained devices

Science.gov (United States)

Ehlers, Johan Hendrik; Jassim, Sabah A.

2007-04-01

The wavelet transform is a powerful tool for image and video processing, useful in a range of applications. This paper is concerned with the efficiency of a certain fast-wavelet-transform (FWT) implementation and several wavelet filters, more suitable for constrained devices. Such constraints are typically found on mobile (cell) phones or personal digital assistants (PDA). These constraints can be a combination of; limited memory, slow floating point operations (compared to integer operations, most often as a result of no hardware support) and limited local storage. Yet these devices are burdened with demanding tasks such as processing a live video or audio signal through on-board capturing sensors. In this paper we present a new wavelet software library, HeatWave, that can be used efficiently for image/video processing/analysis tasks on mobile phones and PDA's. We will demonstrate that HeatWave is suitable for realtime applications with fine control and range to suit transform demands. We shall present experimental results to substantiate these claims. Finally this library is intended to be of real use and applied, hence we considered several well known and common embedded operating system platform differences; such as a lack of common routines or functions, stack limitations, etc. This makes HeatWave suitable for a range of applications and research projects.

Efficient video coding integrating MPEG-2 and picture-rate conversion

NARCIS (Netherlands)

Bruin, de F.J.; Bruls, W.H.A.; Burazerovic, D.; Haan, de G.

2002-01-01

We present an MPEG-2 compliant video codec using picture-rate upconversion during decoding. The upconversion autonomously regenerates major parts of frames without vectorial and residual data. Consequently, the bitrate is greatly reduced.

Analisa Perbandingan Quality of Service Voice Over IP dengan Pengujian Codec Menggunakan Algoritma Low Latency Queuing

Directory of Open Access Journals (Sweden)

Darmawan Darmawan

2017-09-01

Full Text Available Voice over IP (VoIP adalah solusi komunikasi suara yang murah karena menggunakan jaringan IP dibanding penggunaan telephone analog yang banyak memakan biaya. Dalam penerapannya, VoIP mengalami permasalahan karena menggunakan teknologi packet switching yang mana penggunaannya bersamaan dengan paket data sehingga timbul delay, jitter, dan packet loss.  Pada penelitian ini, algoritma Low Latency Queuing (LLQ diterapkan pada router cisco. Algoritma LLQ merupakan gabungan dari algoritma Priority Queuing (PQ dan Class Based Weight Fair Queuing (CBWFQ sehingga dapat memprioritaskan paket suara disamping paket data. Algoritma LLQ ini diujikan menggunakan codec GSM FR, G722, dan G711 A-law. Hasil pengujian didapatkan nilai parameter yang tidak jauh berbeda dan memenuhi standar ITU-T.G1010. Nilai delay rata - rata terendah yaitu ketika menggunakan codec G722 sebesar 20,019 ms tetapi G722 memiliki rata - rata jitter yang terbesar yaitu 0,986 ms.  Codec dengan jitter rata – rata terkecil adalah G711 A-law sebesar 0,838 ms. Packet loss untuk semua codec yang diujikan adalah 0%.  Throughput pada paket data terbesar saat menggunakan codec GSM FR yaitu 18,139 kbps. Codec yang direkomendasikan adalah G711 A-law karena lebih stabil dari segi jitter dan codec GSM FR cocok diimplementasikan pada jaringan yang memiliki bandwitdh kecil.

JPEG XS, a new standard for visually lossless low-latency lightweight image compression

Science.gov (United States)

Descampe, Antonin; Keinert, Joachim; Richter, Thomas; Fößel, Siegfried; Rouvroy, Gaël.

2017-09-01

JPEG XS is an upcoming standard from the JPEG Committee (formally known as ISO/IEC SC29 WG1). It aims to provide an interoperable visually lossless low-latency lightweight codec for a wide range of applications including mezzanine compression in broadcast and Pro-AV markets. This requires optimal support of a wide range of implementation technologies such as FPGAs, CPUs and GPUs. Targeted use cases are professional video links, IP transport, Ethernet transport, real-time video storage, video memory buffers, and omnidirectional video capture and rendering. In addition to the evaluation of the visual transparency of the selected technologies, a detailed analysis of the hardware and software complexity as well as the latency has been done to make sure that the new codec meets the requirements of the above-mentioned use cases. In particular, the end-to-end latency has been constrained to a maximum of 32 lines. Concerning the hardware complexity, neither encoder nor decoder should require more than 50% of an FPGA similar to Xilinx Artix 7 or 25% of an FPGA similar to Altera Cyclon 5. This process resulted in a coding scheme made of an optional color transform, a wavelet transform, the entropy coding of the highest magnitude level of groups of coefficients, and the raw inclusion of the truncated wavelet coefficients. This paper presents the details and status of the standardization process, a technical description of the future standard, and the latest performance evaluation results.

Big data extraction with adaptive wavelet analysis (Presentation Video)

Science.gov (United States)

Qu, Hongya; Chen, Genda; Ni, Yiqing

2015-04-01

Nondestructive evaluation and sensing technology have been increasingly applied to characterize material properties and detect local damage in structures. More often than not, they generate images or data strings that are difficult to see any physical features without novel data extraction techniques. In the literature, popular data analysis techniques include Short-time Fourier Transform, Wavelet Transform, and Hilbert Transform for time efficiency and adaptive recognition. In this study, a new data analysis technique is proposed and developed by introducing an adaptive central frequency of the continuous Morlet wavelet transform so that both high frequency and time resolution can be maintained in a time-frequency window of interest. The new analysis technique is referred to as Adaptive Wavelet Analysis (AWA). This paper will be organized in several sections. In the first section, finite time-frequency resolution limitations in the traditional wavelet transform are introduced. Such limitations would greatly distort the transformed signals with a significant frequency variation with time. In the second section, Short Time Wavelet Transform (STWT), similar to Short Time Fourier Transform (STFT), is defined and developed to overcome such shortcoming of the traditional wavelet transform. In the third section, by utilizing the STWT and a time-variant central frequency of the Morlet wavelet, AWA can adapt the time-frequency resolution requirement to the signal variation over time. Finally, the advantage of the proposed AWA is demonstrated in Section 4 with a ground penetrating radar (GPR) image from a bridge deck, an analytical chirp signal with a large range sinusoidal frequency change over time, the train-induced acceleration responses of the Tsing-Ma Suspension Bridge in Hong Kong, China. The performance of the proposed AWA will be compared with the STFT and traditional wavelet transform.

Mixture block coding with progressive transmission in packet video. Appendix 1: Item 2. M.S. Thesis

Science.gov (United States)

Chen, Yun-Chung

1989-01-01

Video transmission will become an important part of future multimedia communication because of dramatically increasing user demand for video, and rapid evolution of coding algorithm and VLSI technology. Video transmission will be part of the broadband-integrated services digital network (B-ISDN). Asynchronous transfer mode (ATM) is a viable candidate for implementation of B-ISDN due to its inherent flexibility, service independency, and high performance. According to the characteristics of ATM, the information has to be coded into discrete cells which travel independently in the packet switching network. A practical realization of an ATM video codec called Mixture Block Coding with Progressive Transmission (MBCPT) is presented. This variable bit rate coding algorithm shows how a constant quality performance can be obtained according to user demand. Interactions between codec and network are emphasized including packetization, service synchronization, flow control, and error recovery. Finally, some simulation results based on MBCPT coding with error recovery are presented.

Modeling Network Traffic in Wavelet Domain

Directory of Open Access Journals (Sweden)

Sheng Ma

2004-12-01

Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

Encryption for confidentiality of the network and influence of this to the quality of streaming video through network

Science.gov (United States)

Sevcik, L.; Uhrin, D.; Frnda, J.; Voznak, M.; Toral-Cruz, Homer; Mikulec, M.; Jakovlev, Sergej

2015-05-01

Nowadays, the interest in real-time services, like audio and video, is growing. These services are mostly transmitted over packet networks, which are based on IP protocol. It leads to analyses of these services and their behavior in such networks which are becoming more frequent. Video has become the significant part of all data traffic sent via IP networks. In general, a video service is one-way service (except e.g. video calls) and network delay is not such an important factor as in a voice service. Dominant network factors that influence the final video quality are especially packet loss, delay variation and the capacity of the transmission links. Analysis of video quality concentrates on the resistance of video codecs to packet loss in the network, which causes artefacts in the video. IPsec provides confidentiality in terms of safety, integrity and non-repudiation (using HMAC-SHA1 and 3DES encryption for confidentiality and AES in CBC mode) with an authentication header and ESP (Encapsulating Security Payload). The paper brings a detailed view of the performance of video streaming over an IP-based network. We compared quality of video with packet loss and encryption as well. The measured results demonstrated the relation between the video codec type and bitrate to the final video quality.

Temporal Scalability through Adaptive -Band Filter Banks for Robust H.264/MPEG-4 AVC Video Coding

Directory of Open Access Journals (Sweden)

Pau G

2006-01-01

Full Text Available This paper presents different structures that use adaptive -band hierarchical filter banks for temporal scalability. Open-loop and closed-loop configurations are introduced and illustrated using existing video codecs. In particular, it is shown that the H.264/MPEG-4 AVC codec allows us to introduce scalability by frame shuffling operations, thus keeping backward compatibility with the standard. The large set of shuffling patterns introduced here can be exploited to adapt the encoding process to the video content features, as well as to the user equipment and transmission channel characteristics. Furthermore, simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality in error-free environments, while in error-prone channels the scalable versions provide increased robustness.

No Reference Video-Quality-Assessment Model for Monitoring Video Quality of IPTV Services

Science.gov (United States)

Yamagishi, Kazuhisa; Okamoto, Jun; Hayashi, Takanori; Takahashi, Akira

Service providers should monitor the quality of experience of a communication service in real time to confirm its status. To do this, we previously proposed a packet-layer model that can be used for monitoring the average video quality of typical Internet protocol television content using parameters derived from transmitted packet headers. However, it is difficult to monitor the video quality per user using the average video quality because video quality depends on the video content. To accurately monitor the video quality per user, a model that can be used for estimating the video quality per video content rather than the average video quality should be developed. Therefore, to take into account the impact of video content on video quality, we propose a model that calculates the difference in video quality between the video quality of the estimation-target video and the average video quality estimated using a packet-layer model. We first conducted extensive subjective quality assessments for different codecs and video sequences. We then model their characteristics based on parameters related to compression and packet loss. Finally, we verify the performance of the proposed model by applying it to unknown data sets different from the training data sets used for developing the model.

Temporal scalability comparison of the H.264/SVC and distributed video codec

DEFF Research Database (Denmark)

Huang, Xin; Ukhanova, Ann; Belyaev, Evgeny

2009-01-01

The problem of the multimedia scalable video streaming is a current topic of interest. There exist many methods for scalable video coding. This paper is focused on the scalable extension of H.264/AVC (H.264/SVC) and distributed video coding (DVC). The paper presents an efficiency comparison of SV...

Compression evaluation of surgery video recordings retaining diagnostic credibility (compression evaluation of surgery video)

Science.gov (United States)

Duplaga, M.; Leszczuk, M. I.; Papir, Z.; Przelaskowski, A.

2008-12-01

Wider dissemination of medical digital video libraries is affected by two correlated factors, resource effective content compression that directly influences its diagnostic credibility. It has been proved that it is possible to meet these contradictory requirements halfway for long-lasting and low motion surgery recordings at compression ratios close to 100 (bronchoscopic procedures were a case study investigated). As the main supporting assumption, it has been accepted that the content can be compressed as far as clinicians are not able to sense a loss of video diagnostic fidelity (a visually lossless compression). Different market codecs were inspected by means of the combined subjective and objective tests toward their usability in medical video libraries. Subjective tests involved a panel of clinicians who had to classify compressed bronchoscopic video content according to its quality under the bubble sort algorithm. For objective tests, two metrics (hybrid vector measure and hosaka Plots) were calculated frame by frame and averaged over a whole sequence.

78 FR 57648 - Notice of Issuance of Final Determination Concerning Video Teleconferencing Server

Science.gov (United States)

2013-09-19

..., making the ability to infiltrate the unit via eavesdropping or malware through the network connection... connection from malware infiltration. The Video Board, including the codec, is manufactured in China, and has... installation of the LAN connection is to wipe the device clean from any malware residing in the original...

Parallel iterative decoding of transform domain Wyner-Ziv video using cross bitplane correlation

DEFF Research Database (Denmark)

Luong, Huynh Van; Huang, Xin; Forchhammer, Søren

2011-01-01

decoding scheme is proposed to improve the coding efficiency of TDWZ video codecs. The proposed parallel iterative LDPC decoding scheme is able to utilize cross bitplane correlation during decoding, by iteratively refining the soft-input, updating a modeled noise distribution and thereafter enhancing......In recent years, Transform Domain Wyner-Ziv (TDWZ) video coding has been proposed as an efficient Distributed Video Coding (DVC) solution, which fully or partly exploits the source statistics at the decoder to reduce the computational burden at the encoder. In this paper, a parallel iterative LDPC...

Processing Decoded Video for LCD-LED Backlight Display

DEFF Research Database (Denmark)

Nadernejad, Ehsan

The quality of digital images and video signal on visual media such as TV screens and LCD displays is affected by two main factors; the display technology and compression standards. Accurate knowledge about the characteristics of display and the video signal can be utilized to develop advanced...... on local LED-LCD backlight. Second, removing the digital video codec artifacts such as blocking and ringing artifacts by post-processing algorithms. A novel algorithm based on image features with optimal balance between visual quality and power consumption was developed. In addition, to remove flickering...... algorithms for signal (image or video) enhancement. One particular application of such algorithms is the case of LCDs with dynamic local backlight. The thesis addressed two main problems; first, designing algorithms that improve the visual quality of perceived image and video and reduce power consumption...

Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

Directory of Open Access Journals (Sweden)

Lerouge Sam

2007-01-01

Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4 .

Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

Directory of Open Access Journals (Sweden)

Rik Van de Walle

2007-01-01

Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4%.

Energy minimization of mobile video devices with a hardware H.264/AVC encoder based on energy-rate-distortion optimization

Science.gov (United States)

Kang, Donghun; Lee, Jungeon; Jung, Jongpil; Lee, Chul-Hee; Kyung, Chong-Min

2014-09-01

In mobile video systems powered by battery, reducing the encoder's compression energy consumption is critical to prolong its lifetime. Previous Energy-rate-distortion (E-R-D) optimization methods based on a software codec is not suitable for practical mobile camera systems because the energy consumption is too large and encoding rate is too low. In this paper, we propose an E-R-D model for the hardware codec based on the gate-level simulation framework to measure the switching activity and the energy consumption. From the proposed E-R-D model, an energy minimizing algorithm for mobile video camera sensor have been developed with the GOP (Group of Pictures) size and QP(Quantization Parameter) as run-time control variables. Our experimental results show that the proposed algorithm provides up to 31.76% of energy consumption saving while satisfying the rate and distortion constraints.

Web-based remote video monitoring system implemented using Java technology

Science.gov (United States)

Li, Xiaoming

2012-04-01

A HTTP based video transmission system has been built upon the p2p(peer to peer) network structure utilizing the Java technologies. This makes the video monitoring available to any host which has been connected to the World Wide Web in any method, including those hosts behind firewalls or in isolated sub-networking. In order to achieve this, a video source peer has been developed, together with the client video playback peer. The video source peer can respond to the video stream request in HTTP protocol. HTTP based pipe communication model is developed to speeding the transmission of video stream data, which has been encoded into fragments using the JPEG codec. To make the system feasible in conveying video streams between arbitrary peers on the web, a HTTP protocol based relay peer is implemented as well. This video monitoring system has been applied in a tele-robotic system as a visual feedback to the operator.

Wavelet Denoising of Mobile Radiation Data

International Nuclear Information System (INIS)

Campbell, D.B.

2008-01-01

The FY08 phase of this project investigated the merits of video fusion as a method for mitigating the false alarms encountered by vehicle borne detection systems in an effort to realize performance gains associated with wavelet denoising. The fusion strategy exploited the significant correlations which exist between data obtained from radiation detectors and video systems with coincident fields of view. The additional information provided by optical systems can greatly increase the capabilities of these detection systems by reducing the burden of false alarms and through the generation of actionable information. The investigation into the use of wavelet analysis techniques as a means of filtering the gross-counts signal obtained from moving radiation detectors showed promise for vehicle borne systems. However, the applicability of these techniques to man-portable systems is limited due to minimal gains in performance over the rapid feedback available to system operators under walking conditions. Furthermore, the fusion of video holds significant promise for systems operating from vehicles or systems organized into stationary arrays; however, the added complexity and hardware required by this technique renders it infeasible for man-portable systems

Pedestrian detection based on redundant wavelet transform

Science.gov (United States)

Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun

2016-10-01

Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

Network Degradation Effects on Different Codec Types and Characteristics of Video Streaming

Directory of Open Access Journals (Sweden)

Jaroslav Frnda

2014-01-01

Full Text Available Nowadays, there is a quickly growing demand for the transmission of voice, video and data over an IP based network. Multimedia, whether we are talking about broadcast, audio and video transmission and others, from a global perspective is growing exponentially with time. With incoming requests from users, new technologies for data transfer are continually developing. Data must be delivered reliably and with the fewest losses at such high speed. Video quality as part of multimedia technology has a very important role nowadays. It is influenced by several factors, where each of them can have many forms and processing. Network performance is the major degradation effect that influences the quality of resulting image. Poor network performance (lack of link capacity, high network load… causes data packet losses or different delivery time for each packet. This work focuses exactly on these network phenomena. It examines the impact of different delays and packet losses on the quality parameters of triple play services, to evaluate the results using objective methods. The aim of this work is to bring a detailed view on the performance of video streaming over IP-based networks.

Building nonredundant adaptive wavelets by update lifting

NARCIS (Netherlands)

H.J.A.M. Heijmans (Henk); B. Pesquet-Popescu; G. Piella (Gema)

2002-01-01

textabstractAdaptive wavelet decompositions appear useful in various applications in image and video processing, such as image analysis, compression, feature extraction, denoising and deconvolution, or optic flow estimation. For such tasks it may be important that the multiresolution representations

Motion compensation via redundant-wavelet multihypothesis.

Science.gov (United States)

Fowler, James E; Cui, Suxia; Wang, Yonghui

2006-10-01

Multihypothesis motion compensation has been widely used in video coding with previous attention focused on techniques employing predictions that are diverse spatially or temporally. In this paper, the multihypothesis concept is extended into the transform domain by using a redundant wavelet transform to produce multiple predictions that are diverse in transform phase. The corresponding multiple-phase inverse transform implicitly combines the phase-diverse predictions into a single spatial-domain prediction for motion compensation. The performance advantage of this redundant-wavelet-multihypothesis approach is investigated analytically, invoking the fact that the multiple-phase inverse involves a projection that significantly reduces the power of a dense-motion residual modeled as additive noise. The analysis shows that redundant-wavelet multihypothesis is capable of up to a 7-dB reduction in prediction-residual variance over an equivalent single-phase, single-hypothesis approach. Experimental results substantiate the performance advantage for a block-based implementation.

Communicating pictures a course in image and video coding

CERN Document Server

Bull, David R

2014-01-01

Communicating Pictures starts with a unique historical perspective of the role of images in communications and then builds on this to explain the applications and requirements of a modern video coding system. It draws on the author's extensive academic and professional experience of signal processing and video coding to deliver a text that is algorithmically rigorous, yet accessible, relevant to modern standards, and practical. It offers a thorough grounding in visual perception, and demonstrates how modern image and video compression methods can be designed in order to meet the rate-quality performance levels demanded by today's applications, networks and users. With this book you will learn: Practical issues when implementing a codec, such as picture boundary extension and complexity reduction, with particular emphasis on efficient algorithms for transforms, motion estimators and error resilience Conflicts between conventional video compression, based on variable length coding and spatiotemporal prediction,...

Subjective and objective measurement of the intelligibility of synthesized speech impaired by the very low bit rate STANAG 4591 codec including packet loss

NARCIS (Netherlands)

Počta, P.; Beerends, J.G.

2017-01-01

This paper deals with the intelligibility of speech coded by the STANAG 4591 standard codec, including packet loss, using synthesized speech input. Both subjective and objective assessments are used. It is shown that this codec significantly degrades intelligibility when compared to a standard

Transform domain Wyner-Ziv video coding with refinement of noise residue and side information

DEFF Research Database (Denmark)

Huang, Xin; Forchhammer, Søren

2010-01-01

are successively updating the estimated noise residue for noise modeling and side information frame quality during decoding. Experimental results show that the proposed decoder can improve the Rate- Distortion (RD) performance of a state-of-the-art Wyner Ziv video codec for the set of test sequences.......Distributed Video Coding (DVC) is a video coding paradigm which mainly exploits the source statistics at the decoder based on the availability of side information at the decoder. This paper considers feedback channel based Transform Domain Wyner-Ziv (TDWZ) DVC. The coding efficiency of TDWZ video...... coding does not match that of conventional video coding yet, mainly due to the quality of side information and inaccurate noise estimation. In this context, a novel TDWZ video decoder with noise residue refinement (NRR) and side information refinement (SIR) is proposed. The proposed refinement schemes...

A parallel 3-D discrete wavelet transform architecture using pipelined lifting scheme approach for video coding

Science.gov (United States)

Hegde, Ganapathi; Vaya, Pukhraj

2013-10-01

This article presents a parallel architecture for 3-D discrete wavelet transform (3-DDWT). The proposed design is based on the 1-D pipelined lifting scheme. The architecture is fully scalable beyond the present coherent Daubechies filter bank (9, 7). This 3-DDWT architecture has advantages such as no group of pictures restriction and reduced memory referencing. It offers low power consumption, low latency and high throughput. The computing technique is based on the concept that lifting scheme minimises the storage requirement. The application specific integrated circuit implementation of the proposed architecture is done by synthesising it using 65 nm Taiwan Semiconductor Manufacturing Company standard cell library. It offers a speed of 486 MHz with a power consumption of 2.56 mW. This architecture is suitable for real-time video compression even with large frame dimensions.

Impact of the codec and various QoS methods on the final quality of the transferred voice in an IP network

International Nuclear Information System (INIS)

Slavata, Oldřich; Holub, Jan

2015-01-01

This paper deals with an analysis of the relation between the codec that is used, the QoS method, and the final voice transmission quality. The Cisco 2811 router is used for adjusting QoS. VoIP client Linphone is used for adjusting the codec. The criterion for transmission quality is the MOS parameter investigated with the ITU-T P.862 PESQ and P.863 POLQA algorithms

Accelerating wavelet lifting on graphics hardware using CUDA

NARCIS (Netherlands)

Laan, van der W.J.; Roerdink, J.B.T.M.; Jalba, A.C.

2011-01-01

The Discrete Wavelet Transform (DWT) has a wide range of applications from signal processing to video and image compression. We show that this transform, by means of the lifting scheme, can be performed in a memory and computation-efficient way on modern, programmable GPUs, which can be regarded as

Accelerating Wavelet Lifting on Graphics Hardware Using CUDA

NARCIS (Netherlands)

Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B.T.M.

The Discrete Wavelet Transform (DWT) has a wide range of applications from signal processing to video and image compression. We show that this transform, by means of the lifting scheme, can be performed in a memory and computation-efficient way on modern, programmable GPUs, which can be regarded as

ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

Directory of Open Access Journals (Sweden)

I Made Oka Widyantara

2015-12-01

Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG-DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views

A robust fusion method for multiview distributed video coding

DEFF Research Database (Denmark)

Salmistraro, Matteo; Ascenso, Joao; Brites, Catarina

2014-01-01

Distributed video coding (DVC) is a coding paradigm which exploits the redundancy of the source (video) at the decoder side, as opposed to predictive coding, where the encoder leverages the redundancy. To exploit the correlation between views, multiview predictive video codecs require the encoder...... with a robust fusion system able to improve the quality of the fused SI along the decoding process through a learning process using already decoded data. We shall here take the approach to fuse the estimated distributions of the SIs as opposed to a conventional fusion algorithm based on the fusion of pixel...... values. The proposed solution is able to achieve gains up to 0.9 dB in Bjøntegaard difference when compared with the best-performing (in a RD sense) single SI DVC decoder, chosen as the best of an inter-view and a temporal SI-based decoder one....

Video transmission on ATM networks. Ph.D. Thesis

Science.gov (United States)

Chen, Yun-Chung

1993-01-01

The broadband integrated services digital network (B-ISDN) is expected to provide high-speed and flexible multimedia applications. Multimedia includes data, graphics, image, voice, and video. Asynchronous transfer mode (ATM) is the adopted transport techniques for B-ISDN and has the potential for providing a more efficient and integrated environment for multimedia. It is believed that most broadband applications will make heavy use of visual information. The prospect of wide spread use of image and video communication has led to interest in coding algorithms for reducing bandwidth requirements and improving image quality. The major results of a study on the bridging of network transmission performance and video coding are: Using two representative video sequences, several video source models are developed. The fitness of these models are validated through the use of statistical tests and network queuing performance. A dual leaky bucket algorithm is proposed as an effective network policing function. The concept of the dual leaky bucket algorithm can be applied to a prioritized coding approach to achieve transmission efficiency. A mapping of the performance/control parameters at the network level into equivalent parameters at the video coding level is developed. Based on that, a complete set of principles for the design of video codecs for network transmission is proposed.

Non-intrusive Packet-Layer Model for Monitoring Video Quality of IPTV Services

Science.gov (United States)

Yamagishi, Kazuhisa; Hayashi, Takanori

Developing a non-intrusive packet-layer model is required to passively monitor the quality of experience (QoE) during service. We propose a packet-layer model that can be used to estimate the video quality of IPTV using quality parameters derived from transmitted packet headers. The computational load of the model is lighter than that of the model that takes video signals and/or video-related bitstream information such as motion vectors as input. This model is applicable even if the transmitted bitstream information is encrypted because it uses transmitted packet headers rather than bitstream information. For developing the model, we conducted three extensive subjective quality assessments for different encoders and decoders (codecs), and video content. Then, we modeled the subjective video quality assessment characteristics based on objective features affected by coding and packet loss. Finally, we verified the model's validity by applying our model to unknown data sets different from training data sets used above.

Certain problems concerning wavelets and wavelets packets

Energy Technology Data Exchange (ETDEWEB)

Siddiqi, A H

1995-09-01

Wavelets is the outcome of the synthesis of ideas that have emerged in different branches of science and technology, mainly in the last decade. The concept of wavelet packets, which are superpositions of wavelets, has been introduced a couple of years ago. They form bases which retain many properties of wavelets like orthogonality, smoothness and localization. The Walsh orthornomal system is a special case of wavelet packet. The wavelet packets provide at our disposal a library of orthonormal bases, each of which can be used to analyze a given signal of finite energy. The optimal choice is decided by the entropy criterion. In the present paper we discuss results concerning convergence, coefficients, and approximation of wavelet packets series in general and wavelets series in particular. Wavelet packet techniques for solutions of differential equations are also mentioned. (author). 117 refs.

Certain problems concerning wavelets and wavelets packets

International Nuclear Information System (INIS)

Siddiqi, A.H.

1995-09-01

Wavelets is the outcome of the synthesis of ideas that have emerged in different branches of science and technology, mainly in the last decade. The concept of wavelet packets, which are superpositions of wavelets, has been introduced a couple of years ago. They form bases which retain many properties of wavelets like orthogonality, smoothness and localization. The Walsh orthornomal system is a special case of wavelet packet. The wavelet packets provide at our disposal a library of orthonormal bases, each of which can be used to analyze a given signal of finite energy. The optimal choice is decided by the entropy criterion. In the present paper we discuss results concerning convergence, coefficients, and approximation of wavelet packets series in general and wavelets series in particular. Wavelet packet techniques for solutions of differential equations are also mentioned. (author). 117 refs

High-speed low-complexity video coding with EDiCTius: a DCT coding proposal for JPEG XS

Science.gov (United States)

Richter, Thomas; Fößel, Siegfried; Keinert, Joachim; Scherl, Christian

2017-09-01

In its 71th meeting, the JPEG committee issued a call for low complexity, high speed image coding, designed to address the needs of low-cost video-over-ip applications. As an answer to this call, Fraunhofer IIS and the Computing Center of the University of Stuttgart jointly developed an embedded DCT image codec requiring only minimal resources while maximizing throughput on FPGA and GPU implementations. Objective and subjective tests performed for the 73rd meeting confirmed its excellent performance and suitability for its purpose, and it was selected as one of the two key contributions for the development of a joined test model. In this paper, its authors describe the design principles of the codec, provide a high-level overview of the encoder and decoder chain and provide evaluation results on the test corpus selected by the JPEG committee.

Dimensioning Method for Conversational Video Applications in Wireless Convergent Networks

Directory of Open Access Journals (Sweden)

Raquel Perez Leal

2007-12-01

Full Text Available New convergent services are becoming possible, thanks to the expansion of IP networks based on the availability of innovative advanced coding formats such as H.264, which reduce network bandwidth requirements providing good video quality, and the rapid growth in the supply of dual-mode WiFi cellular terminals. This paper provides, first, a comprehensive subject overview as several technologies are involved, such as medium access protocol in IEEE802.11, H.264 advanced video coding standards, and conversational application characterization and recommendations. Second, the paper presents a new and simple dimensioning model of conversational video over wireless LAN. WLAN is addressed under the optimal network throughput and the perspective of video quality. The maximum number of simultaneous users resulting from throughput is limited by the collisions taking place in the shared medium with the statistical contention protocol. The video quality is conditioned by the packet loss in the contention protocol. Both approaches are analyzed within the scope of the advanced video codecs used in conversational video over IP, to conclude that conversational video dimensioning based on network throughput is not enough to ensure a satisfactory user experience, and video quality has to be taken also into account. Finally, the proposed model has been applied to a real-office scenario.

Dimensioning Method for Conversational Video Applications in Wireless Convergent Networks

Directory of Open Access Journals (Sweden)

Alonso JoséI

2008-01-01

Full Text Available Abstract New convergent services are becoming possible, thanks to the expansion of IP networks based on the availability of innovative advanced coding formats such as H.264, which reduce network bandwidth requirements providing good video quality, and the rapid growth in the supply of dual-mode WiFi cellular terminals. This paper provides, first, a comprehensive subject overview as several technologies are involved, such as medium access protocol in IEEE802.11, H.264 advanced video coding standards, and conversational application characterization and recommendations. Second, the paper presents a new and simple dimensioning model of conversational video over wireless LAN. WLAN is addressed under the optimal network throughput and the perspective of video quality. The maximum number of simultaneous users resulting from throughput is limited by the collisions taking place in the shared medium with the statistical contention protocol. The video quality is conditioned by the packet loss in the contention protocol. Both approaches are analyzed within the scope of the advanced video codecs used in conversational video over IP, to conclude that conversational video dimensioning based on network throughput is not enough to ensure a satisfactory user experience, and video quality has to be taken also into account. Finally, the proposed model has been applied to a real-office scenario.

Architectures for radio over fiber transmission of high-quality video and data signals

DEFF Research Database (Denmark)

Lebedev, Alexander

with a constraint on complexity. For wireless personal area networks distribution, we explore the notion of joint optimization of physical layer parameters of a fiber-wireless link (optical power levels, wireless transmission distance) and the codec parameters (quantization, error-resilience tools) based...... on the peak signal-to-noise ratio as an objective video quality metric for compressed video transmission. Furthermore, we experimentally demonstrate uncompressed 1080i highdefinition video distribution in V-band (50–75 GHz) and W-band (75–110 GHz) fiber-wireless links achieving 3 m of wireless transmission...... efficient wired/wireless backhaul of picocell networks. Gigabit signal transmission is realized in combined fiber-wireless-fiber link enabling simultaneous backhaul of dense metropolitan and suburban areas. In this Thesis, we propose a technique to combat periodic chromatic dispersion-induced radio...

Distortion-Based Slice Level Prioritization for Real-Time Video over QoS-Enabled Wireless Networks

Directory of Open Access Journals (Sweden)

Ismail A. Ali

2012-01-01

Full Text Available This paper presents a prioritization scheme based on an analysis of the impact on objective video quality when dropping individual slices from coded video streams. It is shown that giving higher-priority classified packets preference in accessing the wireless media results in considerable quality gain (up to 3 dB in tests over the case when no prioritization is applied. The proposed scheme is demonstrated for an IEEE 802.11e quality-of-service- (QoS- enabled wireless LAN. Though more complex prioritization systems are possible, the proposed scheme is crafted for mobile interactive or user-to-user video services and is simply implemented within the Main or the Baseline profiles of an H.264 codec.

Dual-Layer Video Encryption using RSA Algorithm

Science.gov (United States)

Chadha, Aman; Mallik, Sushmit; Chadha, Ankit; Johar, Ravdeep; Mani Roja, M.

2015-04-01

This paper proposes a video encryption algorithm using RSA and Pseudo Noise (PN) sequence, aimed at applications requiring sensitive video information transfers. The system is primarily designed to work with files encoded using the Audio Video Interleaved (AVI) codec, although it can be easily ported for use with Moving Picture Experts Group (MPEG) encoded files. The audio and video components of the source separately undergo two layers of encryption to ensure a reasonable level of security. Encryption of the video component involves applying the RSA algorithm followed by the PN-based encryption. Similarly, the audio component is first encrypted using PN and further subjected to encryption using the Discrete Cosine Transform. Combining these techniques, an efficient system, invulnerable to security breaches and attacks with favorable values of parameters such as encryption/decryption speed, encryption/decryption ratio and visual degradation; has been put forth. For applications requiring encryption of sensitive data wherein stringent security requirements are of prime concern, the system is found to yield negligible similarities in visual perception between the original and the encrypted video sequence. For applications wherein visual similarity is not of major concern, we limit the encryption task to a single level of encryption which is accomplished by using RSA, thereby quickening the encryption process. Although some similarity between the original and encrypted video is observed in this case, it is not enough to comprehend the happenings in the video.

Discovering Wavelets

CERN Document Server

Aboufadel, Edward

1999-01-01

An accessible and practical introduction to wavelets. With applications in image processing, audio restoration, seismology, and elsewhere, wavelets have been the subject of growing excitement and interest over the past several years. Unfortunately, most books on wavelets are accessible primarily to research mathematicians. Discovering Wavelets presents basic and advanced concepts of wavelets in a way that is accessible to anyone with only a fundamental knowledge of linear algebra. The basic concepts of wavelet theory are introduced in the context of an explanation of how the FBI uses wavelets

Joint source/channel coding of scalable video over noisy channels

Energy Technology Data Exchange (ETDEWEB)

Cheung, G.; Zakhor, A. [Department of Electrical Engineering and Computer Sciences University of California Berkeley, California94720 (United States)

1997-01-01

We propose an optimal bit allocation strategy for a joint source/channel video codec over noisy channel when the channel state is assumed to be known. Our approach is to partition source and channel coding bits in such a way that the expected distortion is minimized. The particular source coding algorithm we use is rate scalable and is based on 3D subband coding with multi-rate quantization. We show that using this strategy, transmission of video over very noisy channels still renders acceptable visual quality, and outperforms schemes that use equal error protection only. The flexibility of the algorithm also permits the bit allocation to be selected optimally when the channel state is in the form of a probability distribution instead of a deterministic state. {copyright} {ital 1997 American Institute of Physics.}

Video Error Correction Using Steganography

Science.gov (United States)

Robie, David L.; Mersereau, Russell M.

2002-12-01

The transmission of any data is always subject to corruption due to errors, but video transmission, because of its real time nature must deal with these errors without retransmission of the corrupted data. The error can be handled using forward error correction in the encoder or error concealment techniques in the decoder. This MPEG-2 compliant codec uses data hiding to transmit error correction information and several error concealment techniques in the decoder. The decoder resynchronizes more quickly with fewer errors than traditional resynchronization techniques. It also allows for perfect recovery of differentially encoded DCT-DC components and motion vectors. This provides for a much higher quality picture in an error-prone environment while creating an almost imperceptible degradation of the picture in an error-free environment.

Deep Learning for Detection of Object-Based Forgery in Advanced Video

Directory of Open Access Journals (Sweden)

Ye Yao

2017-12-01

Full Text Available Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based forgery in the advanced video. The presented deep learning approach utilizes a convolutional neural network (CNN to automatically extract high-dimension features from the input image patches. Different from the traditional CNN models used in computer vision domain, we let video frames go through three preprocessing layers before being fed into our CNN model. They include a frame absolute difference layer to cut down temporal redundancy between video frames, a max pooling layer to reduce computational complexity of image convolution, and a high-pass filter layer to enhance the residual signal left by video forgery. In addition, an asymmetric data augmentation strategy has been established to get a similar number of positive and negative image patches before the training. The experiments have demonstrated that the proposed CNN-based model with the preprocessing layers has achieved excellent results.

Performance and Complexity Co-evaluation of the Advanced Video Coding Standard for Cost-Effective Multimedia Communications

Directory of Open Access Journals (Sweden)

Saponara Sergio

2004-01-01

Full Text Available The advanced video codec (AVC standard, recently defined by a joint video team (JVT of ITU-T and ISO/IEC, is introduced in this paper together with its performance and complexity co-evaluation. While the basic framework is similar to the motion-compensated hybrid scheme of previous video coding standards, additional tools improve the compression efficiency at the expense of an increased implementation cost. As a first step to bridge the gap between the algorithmic design of a complex multimedia system and its cost-effective realization, a high-level co-evaluation approach is proposed and applied to a real-life AVC design. An exhaustive analysis of the codec compression efficiency versus complexity (memory and computational costs project space is carried out at the early algorithmic design phase. If all new coding features are used, the improved AVC compression efficiency (up to 50% compared to current video coding technology comes with a complexity increase of a factor 2 for the decoder and larger than one order of magnitude for the encoder. This represents a challenge for resource-constrained multimedia systems such as wireless devices or high-volume consumer electronics. The analysis also highlights important properties of the AVC framework allowing for complexity reduction at the high system level: when combining the new coding features, the implementation complexity accumulates, while the global compression efficiency saturates. Thus, a proper use of the AVC tools maintains the same performance as the most complex configuration while considerably reducing complexity. The reported results provide inputs to assist the profile definition in the standard, highlight the AVC bottlenecks, and select optimal trade-offs between algorithmic performance and complexity.

Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption

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Jeyamala Chandrasekaran

2015-01-01

Full Text Available Owing to the growth of high performance network technologies, multimedia applications over the Internet are increasing exponentially. Applications like video conferencing, video-on-demand, and pay-per-view depend upon encryption algorithms for providing confidentiality. Video communication is characterized by distinct features such as large volume, high redundancy between adjacent frames, video codec compliance, syntax compliance, and application specific requirements. Naive approaches for video encryption encrypt the entire video stream with conventional text based cryptographic algorithms. Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. This research work aims at enhancing the speed of naive approaches through chaos based S-box design. Chaotic equations are popularly known for randomness, extreme sensitivity to initial conditions, and ergodicity. The proposed methodology employs two-dimensional discrete Henon map for (i generation of dynamic and key-dependent S-box that could be integrated with symmetric algorithms like Blowfish and Data Encryption Standard (DES and (ii generation of one-time keys for simple substitution ciphers. The proposed design is tested for randomness, nonlinearity, avalanche effect, bit independence criterion, and key sensitivity. Experimental results confirm that chaos based S-box design and key generation significantly reduce the computational cost of video encryption with no compromise in security.

Detection of seismic phases by wavelet transform. Dependence of its performance on wavelet functions; Wavelet henkan ni yoru jishinha no iso kenshutsu. Wavelet ni yoru sai

Energy Technology Data Exchange (ETDEWEB)

Zeng, X; Yamazaki, K [Tokyo Gakugei University, Tokyo (Japan); Oguchi, Y [Hosei University, Tokyo (Japan)

1997-10-22

A study has been performed on wavelet analysis of seismic waves. In the wavelet analysis of seismic waves, there is a possibility that the results according to different wavelet functions may come out with great difference. The study has carried out the following analyses: an analysis of amplitude and phase using wavelet transform which uses wavelet function of Morlet on P- and S-waves generated by natural earthquakes and P-wave generated by an artificial earthquake, and an analysis using continuous wavelet transform, which uses a constitution of complex wavelet function constructed by a completely diagonal scaling function of Daubechies and the wavelet function. As a result, the following matters were made clear: the result of detection of abnormal components or discontinuity depends on the wavelet function; if the Morlet wavelet function is used to properly select angular frequency and scale, equiphase lines in a phase scalogram concentrate on the discontinuity; and the result of applying the complex wavelet function is superior to that of applying the wavelet function of Morlet. 2 refs., 5 figs.

Video Error Correction Using Steganography

Directory of Open Access Journals (Sweden)

Robie David L

2002-01-01

Full Text Available The transmission of any data is always subject to corruption due to errors, but video transmission, because of its real time nature must deal with these errors without retransmission of the corrupted data. The error can be handled using forward error correction in the encoder or error concealment techniques in the decoder. This MPEG-2 compliant codec uses data hiding to transmit error correction information and several error concealment techniques in the decoder. The decoder resynchronizes more quickly with fewer errors than traditional resynchronization techniques. It also allows for perfect recovery of differentially encoded DCT-DC components and motion vectors. This provides for a much higher quality picture in an error-prone environment while creating an almost imperceptible degradation of the picture in an error-free environment.

Error and Congestion Resilient Video Streaming over Broadband Wireless

Directory of Open Access Journals (Sweden)

Laith Al-Jobouri

2015-04-01

Full Text Available In this paper, error resilience is achieved by adaptive, application-layer rateless channel coding, which is used to protect H.264/Advanced Video Coding (AVC codec data-partitioned videos. A packetization strategy is an effective tool to control error rates and, in the paper, source-coded data partitioning serves to allocate smaller packets to more important compressed video data. The scheme for doing this is applied to real-time streaming across a broadband wireless link. The advantages of rateless code rate adaptivity are then demonstrated in the paper. Because the data partitions of a video slice are each assigned to different network packets, in congestion-prone wireless networks the increased number of packets per slice and their size disparity may increase the packet loss rate from buffer overflows. As a form of congestion resilience, this paper recommends packet-size dependent scheduling as a relatively simple way of alleviating the buffer-overflow problem arising from data-partitioned packets. The paper also contributes an analysis of data partitioning and packet sizes as a prelude to considering scheduling regimes. The combination of adaptive channel coding and prioritized packetization for error resilience with packet-size dependent packet scheduling results in a robust streaming scheme specialized for broadband wireless and real-time streaming applications such as video conferencing, video telephony, and telemedicine.

Wavelet analysis

CERN Document Server

Cheng, Lizhi; Luo, Yong; Chen, Bo

2014-01-01

This book could be divided into two parts i.e. fundamental wavelet transform theory and method and some important applications of wavelet transform. In the first part, as preliminary knowledge, the Fourier analysis, inner product space, the characteristics of Haar functions, and concepts of multi-resolution analysis, are introduced followed by a description on how to construct wavelet functions both multi-band and multi wavelets, and finally introduces the design of integer wavelets via lifting schemes and its application to integer transform algorithm. In the second part, many applications are discussed in the field of image and signal processing by introducing other wavelet variants such as complex wavelets, ridgelets, and curvelets. Important application examples include image compression, image denoising/restoration, image enhancement, digital watermarking, numerical solution of partial differential equations, and solving ill-conditioned Toeplitz system. The book is intended for senior undergraduate stude...

Management of speech and video telephony quality in heterogeneous wireless networks

CERN Document Server

Lewcio, Błażej

2014-01-01

This book shows how networking research and quality engineering can be combined to successfully manage the transmission quality when speech and video telephony is delivered in heterogeneous wireless networks. Nomadic use of services requires intelligent management of ongoing transmission, and to make the best of available resources many fundamental trade-offs must be considered. Network coverage versus throughput and reliability of a connection is one key aspect, efficiency versus robustness of signal compression is another. However, to successfully manage services, user-perceived Quality of Experience (QoE) in heterogeneous networks must be known, and the perception of quality changes must be understood.  These issues are addressed in this book, in particular focusing on the perception of quality changes due to switching between diverse networks, speech and video codecs, and encoding bit rates during active calls.

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation.

Science.gov (United States)

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-15

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Adaptive distributed video coding with correlation estimation using expectation propagation

Science.gov (United States)

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Reconfiguring waveguide-gratings-based M-signature codecs to enhance OCDMA network confidentiality

Science.gov (United States)

Huang, Jen-Fa; Chen, Kai-Sheng; Lin, Ying-Chen; Li, Chung-Yu

2014-02-01

A reconfiguration scheme based on composite signature codes over waveguide-gratings-based optical code-division multiple-access (OCDMA) network coder/decoders (codecs) is proposed in the paper. By using central control node to monitor network traffic condition and reconfigure the composite signature codes made up of maximal-length sequence (M-sequence) component codes and random changing the signature codes assigned for each user to improve the confidentiality performance in an OCDMA system. The proposed scheme is analyzed with some practical eavesdroppers' attacks.

Content-based video indexing and searching with wavelet transformation

Science.gov (United States)

Stumpf, Florian; Al-Jawad, Naseer; Du, Hongbo; Jassim, Sabah

2006-05-01

Biometric databases form an essential tool in the fight against international terrorism, organised crime and fraud. Various government and law enforcement agencies have their own biometric databases consisting of combination of fingerprints, Iris codes, face images/videos and speech records for an increasing number of persons. In many cases personal data linked to biometric records are incomplete and/or inaccurate. Besides, biometric data in different databases for the same individual may be recorded with different personal details. Following the recent terrorist atrocities, law enforcing agencies collaborate more than before and have greater reliance on database sharing. In such an environment, reliable biometric-based identification must not only determine who you are but also who else you are. In this paper we propose a compact content-based video signature and indexing scheme that can facilitate retrieval of multiple records in face biometric databases that belong to the same person even if their associated personal data are inconsistent. We shall assess the performance of our system using a benchmark audio visual face biometric database that has multiple videos for each subject but with different identity claims. We shall demonstrate that retrieval of relatively small number of videos that are nearest, in terms of the proposed index, to any video in the database results in significant proportion of that individual biometric data.

Low-Cost Super-Resolution Algorithms Implementation Over a HW/SW Video Compression Platform

Directory of Open Access Journals (Sweden)

Llopis Rafael Peset

2006-01-01

Full Text Available Two approaches are presented in this paper to improve the quality of digital images over the sensor resolution using super-resolution techniques: iterative super-resolution (ISR and noniterative super-resolution (NISR algorithms. The results show important improvements in the image quality, assuming that sufficient sample data and a reasonable amount of aliasing are available at the input images. These super-resolution algorithms have been implemented over a codesign video compression platform developed by Philips Research, performing minimal changes on the overall hardware architecture. In this way, a novel and feasible low-cost implementation has been obtained by using the resources encountered in a generic hybrid video encoder. Although a specific video codec platform has been used, the methodology presented in this paper is easily extendable to any other video encoder architectures. Finally a comparison in terms of memory, computational load, and image quality for both algorithms, as well as some general statements about the final impact of the sampling process on the quality of the super-resolved (SR image, are also presented.

ViBee - algoritmo de segmentação aplicado na compressão de vídeos em Weblabs de abelhas

Directory of Open Access Journals (Sweden)

Andre Riyuiti Hirakawa

2009-01-01

videos, CODEC (MPEG4 and WMV, applied to videos of bees reduce the bitrates, as well as the quality, what makes impracticable the applications for the Webbee. Therefore, this paper presents the proposal of a new algorithm for codification of video of bees and the reduction of bitrates, maintaining the quality of the information. The algorithm includes the video segmentation process by identification, recognition and tracking of objects. The test results show an adaptation of the proposal with reduction of data equivalent to the commercial CODECs, with 93% of similarity.

MEKANISME SEGMENTASI LAJU BIT PADA DYNAMIC ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

Directory of Open Access Journals (Sweden)

Muhammad Audy Bazly

2015-12-01

Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG- DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views

Video Browsing on Handheld Devices

Science.gov (United States)

Hürst, Wolfgang

Recent improvements in processing power, storage space, and video codec development enable users now to playback video on their handheld devices in a reasonable quality. However, given the form factor restrictions of such a mobile device, screen size still remains a natural limit and - as the term "handheld" implies - always will be a critical resource. This is not only true for video but any data that is processed on such devices. For this reason, developers have come up with new and innovative ways to deal with large documents in such limited scenarios. For example, if you look at the iPhone, innovative techniques such as flicking have been introduced to skim large lists of text (e.g. hundreds of entries in your music collection). Automatically adapting the zoom level to, for example, the width of table cells when double tapping on the screen enables reasonable browsing of web pages that have originally been designed for large, desktop PC sized screens. A multi touch interface allows you to easily zoom in and out of large text documents and images using two fingers. In the next section, we will illustrate that advanced techniques to browse large video files have been developed in the past years, as well. However, if you look at state-of-the-art video players on mobile devices, normally just simple, VCR like controls are supported (at least at the time of this writing) that only allow users to just start, stop, and pause video playback. If supported at all, browsing and navigation functionality is often restricted to simple skipping of chapters via two single buttons for backward and forward navigation and a small and thus not very sensitive timeline slider.

A Complete Video Coding Chain Based on Multi-Dimensional Discrete Cosine Transform

Directory of Open Access Journals (Sweden)

T. Fryza

2010-09-01

Full Text Available The paper deals with a video compression method based on the multi-dimensional discrete cosine transform. In the text, the encoder and decoder architectures including the definitions of all mathematical operations like the forward and inverse 3-D DCT, quantization and thresholding are presented. According to the particular number of currently processed pictures, the new quantization tables and entropy code dictionaries are proposed in the paper. The practical properties of the 3-D DCT coding chain compared with the modern video compression methods (such as H.264 and WebM and the computing complexity are presented as well. It will be proved the best compress properties could be achieved by complex H.264 codec. On the other hand the computing complexity - especially on the encoding side - is lower for the 3-D DCT method.

Significance tests for the wavelet cross spectrum and wavelet linear coherence

Directory of Open Access Journals (Sweden)

Z. Ge

2008-12-01

Full Text Available This work attempts to develop significance tests for the wavelet cross spectrum and the wavelet linear coherence as a follow-up study on Ge (2007. Conventional approaches that are used by Torrence and Compo (1998 based on stationary background noise time series were used here in estimating the sampling distributions of the wavelet cross spectrum and the wavelet linear coherence. The sampling distributions are then used for establishing significance levels for these two wavelet-based quantities. In addition to these two wavelet quantities, properties of the phase angle of the wavelet cross spectrum of, or the phase difference between, two Gaussian white noise series are discussed. It is found that the tangent of the principal part of the phase angle approximately has a standard Cauchy distribution and the phase angle is uniformly distributed, which makes it impossible to establish significance levels for the phase angle. The simulated signals clearly show that, when there is no linear relation between the two analysed signals, the phase angle disperses into the entire range of [−π,π] with fairly high probabilities for values close to ±π to occur. Conversely, when linear relations are present, the phase angle of the wavelet cross spectrum settles around an associated value with considerably reduced fluctuations. When two signals are linearly coupled, their wavelet linear coherence will attain values close to one. The significance test of the wavelet linear coherence can therefore be used to complement the inspection of the phase angle of the wavelet cross spectrum. The developed significance tests are also applied to actual data sets, simultaneously recorded wind speed and wave elevation series measured from a NOAA buoy on Lake Michigan. Significance levels of the wavelet cross spectrum and the wavelet linear coherence between the winds and the waves reasonably separated meaningful peaks from those generated by randomness in the data set. As

Practical and Scalable Transmission of Segmented Video Sequences to Multiple Players Using H.264

Science.gov (United States)

Quax, Peter; di Fiore, Fabian; Issaris, Panagiotis; Lamotte, Wim; van Reeth, Frank

We present a practical way to distribute viewports on the same video sequence to large amounts of players. Each of them has personal preferences to be met or is limited by the physical properties of his/her device (e.g., screen size of a PDA or processing power of a mobile phone). Instead of taking the naïve approach, in which sections of the video sequence are decoded and re-encoded for each of the clients, we have exploited advanced features offered by the H.264 codec to enable selection of parts of the video sequence by directly manipulating the encoder-generated bitstream. At the same time, we have overcome several practical issues presented by the fact that support for these features is sadly lacking from the state-of-the-art encoders available on the market. Two alternative solutions are discussed and have been implemented, enabling the generation of measurement results and comparison to alternative approaches.

Innovative Video Diagnostic Equipment for Material Science

Science.gov (United States)

Capuano, G.; Titomanlio, D.; Soellner, W.; Seidel, A.

2012-01-01

Materials science experiments under microgravity increasingly rely on advanced optical systems to determine the physical properties of the samples under investigation. This includes video systems with high spatial and temporal resolution. The acquisition, handling, storage and transmission to ground of the resulting video data are very challenging. Since the available downlink data rate is limited, the capability to compress the video data significantly without compromising the data quality is essential. We report on the development of a Digital Video System (DVS) for EML (Electro Magnetic Levitator) which provides real-time video acquisition, high compression using advanced Wavelet algorithms, storage and transmission of a continuous flow of video with different characteristics in terms of image dimensions and frame rates. The DVS is able to operate with the latest generation of high-performance cameras acquiring high resolution video images up to 4Mpixels@60 fps or high frame rate video images up to about 1000 fps@512x512pixels.

Wavelet basics

CERN Document Server

Chan, Y T

1995-01-01

Since the study of wavelets is a relatively new area, much of the research coming from mathematicians, most of the literature uses terminology, concepts and proofs that may, at times, be difficult and intimidating for the engineer. Wavelet Basics has therefore been written as an introductory book for scientists and engineers. The mathematical presentation has been kept simple, the concepts being presented in elaborate detail in a terminology that engineers will find familiar. Difficult ideas are illustrated with examples which will also aid in the development of an intuitive insight. Chapter 1 reviews the basics of signal transformation and discusses the concepts of duals and frames. Chapter 2 introduces the wavelet transform, contrasts it with the short-time Fourier transform and clarifies the names of the different types of wavelet transforms. Chapter 3 links multiresolution analysis, orthonormal wavelets and the design of digital filters. Chapter 4 gives a tour d'horizon of topics of current interest: wave...

Wavelets in neuroscience

CERN Document Server

Hramov, Alexander E; Makarov, Valeri A; Pavlov, Alexey N; Sitnikova, Evgenia

2015-01-01

This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing in detail different practical applications of the wavelet theory in the areas of neurodynamics and neurophysiology and providing a review of fundamental work that has been carried out in these fields over the last decade. Chapters 1 and 2 introduce and review the relevant foundations of neurophysics and wavelet theory, respectively, pointing on one hand to the various current challenges in neuroscience and introducing on the other the mathematical techniques of the wavelet transform in its two variants (discrete and continuous) as a powerful and versatile tool for investigating the relevant neuronal dynamics. Chapter 3 then analyzes results from examining individual neuron dynamics and intracellular processes. The principles for recognizing neuronal spikes from extracellular recordings and the advantages of using wavelets to address these issues are described and combined with approaches based on wavelet neural ...

Multivariate wavelet frames

CERN Document Server

Skopina, Maria; Protasov, Vladimir

2016-01-01

This book presents a systematic study of multivariate wavelet frames with matrix dilation, in particular, orthogonal and bi-orthogonal bases, which are a special case of frames. Further, it provides algorithmic methods for the construction of dual and tight wavelet frames with a desirable approximation order, namely compactly supported wavelet frames, which are commonly required by engineers. It particularly focuses on methods of constructing them. Wavelet bases and frames are actively used in numerous applications such as audio and graphic signal processing, compression and transmission of information. They are especially useful in image recovery from incomplete observed data due to the redundancy of frame systems. The construction of multivariate wavelet frames, especially bases, with desirable properties remains a challenging problem as although a general scheme of construction is well known, its practical implementation in the multidimensional setting is difficult. Another important feature of wavelet is ...

Let's Meet at the Mobile - Learning Dialogs with a Video Conferencing Software for Mobile Devices

Directory of Open Access Journals (Sweden)

Hans L. Cycon

2009-07-01

Full Text Available Mobile phones and related gadgets in networks are omnipresent at our students, advertising itself as the platform for mobile, pervasive learning. Currently, these devices rapidly open and enhance, being soon able to serve as a major platform for rich, open multimedia applications and communication. In this report we introduce a video conferencing software, which seamlessly integrates mobile with stationary users into fully distributed multi-party conversations. Following the paradigm of flexible, user-initiated group communication, we present an integrated solution, which scales well for medium-size conferences and accounts for the heterogeneous nature of mobile and stationary participants. This approach allows for a spontaneous, location independent establishment of video dialogs, which is of particular importance in interactive learning scenarios. The work is based on a highly optimized realization of a H.264 codec.

Video on the Internet: An introduction to the digital encoding, compression, and transmission of moving image data.

Science.gov (United States)

Boudier, T; Shotton, D M

1999-01-01

In this paper, we seek to provide an introduction to the fast-moving field of digital video on the Internet, from the viewpoint of the biological microscopist who might wish to store or access videos, for instance in image databases such as the BioImage Database (http://www.bioimage.org). We describe and evaluate the principal methods used for encoding and compressing moving image data for digital storage and transmission over the Internet, which involve compromises between compression efficiency and retention of image fidelity, and describe the existing alternate software technologies for downloading or streaming compressed digitized videos using a Web browser. We report the results of experiments on video microscopy recordings and three-dimensional confocal animations of biological specimens to evaluate the compression efficiencies of the principal video compression-decompression algorithms (codecs) and to document the artefacts associated with each of them. Because MPEG-1 gives very high compression while yet retaining reasonable image quality, these studies lead us to recommend that video databases should store both a high-resolution original version of each video, ideally either uncompressed or losslessly compressed, and a separate edited and highly compressed MPEG-1 preview version that can be rapidly downloaded for interactive viewing by the database user. Copyright 1999 Academic Press.

Dynamic resource allocation engine for cloud-based real-time video transcoding in mobile cloud computing environments

Science.gov (United States)

Adedayo, Bada; Wang, Qi; Alcaraz Calero, Jose M.; Grecos, Christos

2015-02-01

The recent explosion in video-related Internet traffic has been driven by the widespread use of smart mobile devices, particularly smartphones with advanced cameras that are able to record high-quality videos. Although many of these devices offer the facility to record videos at different spatial and temporal resolutions, primarily with local storage considerations in mind, most users only ever use the highest quality settings. The vast majority of these devices are optimised for compressing the acquired video using a single built-in codec and have neither the computational resources nor battery reserves to transcode the video to alternative formats. This paper proposes a new low-complexity dynamic resource allocation engine for cloud-based video transcoding services that are both scalable and capable of being delivered in real-time. Firstly, through extensive experimentation, we establish resource requirement benchmarks for a wide range of transcoding tasks. The set of tasks investigated covers the most widely used input formats (encoder type, resolution, amount of motion and frame rate) associated with mobile devices and the most popular output formats derived from a comprehensive set of use cases, e.g. a mobile news reporter directly transmitting videos to the TV audience of various video format requirements, with minimal usage of resources both at the reporter's end and at the cloud infrastructure end for transcoding services.

Wavelets and their uses

International Nuclear Information System (INIS)

Dremin, Igor M; Ivanov, Oleg V; Nechitailo, Vladimir A

2001-01-01

This review paper is intended to give a useful guide for those who want to apply the discrete wavelet transform in practice. The notion of wavelets and their use in practical computing and various applications are briefly described, but rigorous proofs of mathematical statements are omitted, and the reader is just referred to the corresponding literature. The multiresolution analysis and fast wavelet transform have become a standard procedure for dealing with discrete wavelets. The proper choice of a wavelet and use of nonstandard matrix multiplication are often crucial for the achievement of a goal. Analysis of various functions with the help of wavelets allows one to reveal fractal structures, singularities etc. The wavelet transform of operator expressions helps solve some equations. In practical applications one often deals with the discretized functions, and the problem of stability of the wavelet transform and corresponding numerical algorithms becomes important. After discussing all these topics we turn to practical applications of the wavelet machinery. They are so numerous that we have to limit ourselves to a few examples only. The authors would be grateful for any comments which would move us closer to the goal proclaimed in the first phrase of the abstract. (reviews of topical problems)

EBLAST: an efficient high-compression image transformation 3. application to Internet image and video transmission

Science.gov (United States)

Schmalz, Mark S.; Ritter, Gerhard X.; Caimi, Frank M.

2001-12-01

A wide variety of digital image compression transforms developed for still imaging and broadcast video transmission are unsuitable for Internet video applications due to insufficient compression ratio, poor reconstruction fidelity, or excessive computational requirements. Examples include hierarchical transforms that require all, or large portion of, a source image to reside in memory at one time, transforms that induce significant locking effect at operationally salient compression ratios, and algorithms that require large amounts of floating-point computation. The latter constraint holds especially for video compression by small mobile imaging devices for transmission to, and compression on, platforms such as palmtop computers or personal digital assistants (PDAs). As Internet video requirements for frame rate and resolution increase to produce more detailed, less discontinuous motion sequences, a new class of compression transforms will be needed, especially for small memory models and displays such as those found on PDAs. In this, the third series of papers, we discuss the EBLAST compression transform and its application to Internet communication. Leading transforms for compression of Internet video and still imagery are reviewed and analyzed, including GIF, JPEG, AWIC (wavelet-based), wavelet packets, and SPIHT, whose performance is compared with EBLAST. Performance analysis criteria include time and space complexity and quality of the decompressed image. The latter is determined by rate-distortion data obtained from a database of realistic test images. Discussion also includes issues such as robustness of the compressed format to channel noise. EBLAST has been shown to perform superiorly to JPEG and, unlike current wavelet compression transforms, supports fast implementation on embedded processors with small memory models.

Adaptive Wavelet Transforms

Energy Technology Data Exchange (ETDEWEB)

Szu, H.; Hsu, C. [Univ. of Southwestern Louisiana, Lafayette, LA (United States)

1996-12-31

Human sensors systems (HSS) may be approximately described as an adaptive or self-learning version of the Wavelet Transforms (WT) that are capable to learn from several input-output associative pairs of suitable transform mother wavelets. Such an Adaptive WT (AWT) is a redundant combination of mother wavelets to either represent or classify inputs.

HIERARCHICAL ADAPTIVE ROOD PATTERN SEARCH FOR MOTION ESTIMATION AT VIDEO SEQUENCE ANALYSIS

Directory of Open Access Journals (Sweden)

V. T. Nguyen

2016-05-01

Full Text Available Subject of Research.The paper deals with the motion estimation algorithms for the analysis of video sequences in compression standards MPEG-4 Visual and H.264. Anew algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. Method. Thealgorithm is called hierarchical adaptive rood pattern search (Hierarchical ARPS, HARPS. This new algorithm includes the classic adaptive rood pattern search ARPS and hierarchical search MP (Hierarchical search or Mean pyramid. All motion estimation algorithms have been implemented using MATLAB package and tested with several video sequences. Main Results. The criteria for evaluating the algorithms were: speed, peak signal to noise ratio, mean square error and mean absolute deviation. The proposed method showed a much better performance at a comparable error and deviation. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms so it requires further investigation. Practical Relevance. Application of this algorithm in MPEG-4 and H.264 codecs instead of the standard can significantly reduce compression time. This feature enables to recommend it in telecommunication systems for multimedia data storing, transmission and processing.

Wavelet Transforms using VTK-m

Energy Technology Data Exchange (ETDEWEB)

Li, Shaomeng [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sewell, Christopher Meyer [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-27

These are a set of slides that deal with the topics of wavelet transforms using VTK-m. First, wavelets are discussed and detailed, then VTK-m is discussed and detailed, then wavelets and VTK-m are looked at from a performance comparison, then from an accuracy comparison, and finally lessons learned, conclusion, and what is next. Lessons learned are the following: Launching worklets is expensive; Natural logic of performing 2D wavelet transform: Repeat the same 1D wavelet transform on every row, repeat the same 1D wavelet transform on every column, invoke the 1D wavelet worklet every time: num_rows x num_columns; VTK-m approach of performing 2D wavelet transform: Create a worklet for 2D that handles both rows and columns, invoke this new worklet only one time; Fast calculation, but cannot reuse 1D implementations.

Wavelets in scientific computing

DEFF Research Database (Denmark)

Nielsen, Ole Møller

1998-01-01

the FWT can be used as a front-end for efficient image compression schemes. Part II deals with vector-parallel implementations of several variants of the Fast Wavelet Transform. We develop an efficient and scalable parallel algorithm for the FWT and derive a model for its performance. Part III...... supported wavelets in the context of multiresolution analysis. These wavelets are particularly attractive because they lead to a stable and very efficient algorithm, namely the fast wavelet transform (FWT). We give estimates for the approximation characteristics of wavelets and demonstrate how and why...... is an investigation of the potential for using the special properties of wavelets for solving partial differential equations numerically. Several approaches are identified and two of them are described in detail. The algorithms developed are applied to the nonlinear Schrödinger equation and Burgers' equation...

Lecture notes on wavelet transforms

CERN Document Server

Debnath, Lokenath

2017-01-01

This book provides a systematic exposition of the basic ideas and results of wavelet analysis suitable for mathematicians, scientists, and engineers alike. The primary goal of this text is to show how different types of wavelets can be constructed, illustrate why they are such powerful tools in mathematical analysis, and demonstrate their use in applications. It also develops the required analytical knowledge and skills on the part of the reader, rather than focus on the importance of more abstract formulation with full mathematical rigor.  These notes differs from many textbooks with similar titles in that a major emphasis is placed on the thorough development of the underlying theory before introducing applications and modern topics such as fractional Fourier transforms, windowed canonical transforms, fractional wavelet transforms, fast wavelet transforms, spline wavelets, Daubechies wavelets, harmonic wavelets and non-uniform wavelets. The selection, arrangement, and presentation of the material in these ...

Recognizing emotions from EEG subbands using wavelet analysis.

Science.gov (United States)

Candra, Henry; Yuwono, Mitchell; Handojoseno, Ardi; Chai, Rifai; Su, Steven; Nguyen, Hung T

2015-01-01

Objectively recognizing emotions is a particularly important task to ensure that patients with emotional symptoms are given the appropriate treatments. The aim of this study was to develop an emotion recognition system using Electroencephalogram (EEG) signals to identify four emotions including happy, sad, angry, and relaxed. We approached this objective by firstly investigating the relevant EEG frequency band followed by deciding the appropriate feature extraction method. Two features were considered namely: 1. Wavelet Energy, and 2. Wavelet Entropy. EEG Channels reduction was then implemented to reduce the complexity of the features. The ground truth emotional states of each subject were inferred using Russel's circumplex model of emotion, that is, by mapping the subjectively reported degrees of valence (pleasure) and arousal to the appropriate emotions - for example, an emotion with high valence and high arousal is equivalent to a `happy' emotional state, while low valence and low arousal is equivalent to a `sad' emotional state. The Support Vector Machine (SVM) classifier was then used for mapping each feature vector into corresponding discrete emotions. The results presented in this study indicated thatWavelet features extracted from alpha, beta and gamma bands seem to provide the necessary information for describing the aforementioned emotions. Using the DEAP (Dataset for Emotion Analysis using electroencephalogram, Physiological and Video Signals), our proposed method achieved an average sensitivity and specificity of 77.4% ± 14.1% and 69.1% ± 12.8%, respectively.

PERFORMANCE ANALYSIS OF SET PARTITIONING IN HIERARCHICAL TREES (SPIHT ALGORITHM FOR A FAMILY OF WAVELETS USED IN COLOR IMAGE COMPRESSION

Directory of Open Access Journals (Sweden)

A. Sreenivasa Murthy

2014-11-01

Full Text Available With the spurt in the amount of data (Image, video, audio, speech, & text available on the net, there is a huge demand for memory & bandwidth savings. One has to achieve this, by maintaining the quality & fidelity of the data acceptable to the end user. Wavelet transform is an important and practical tool for data compression. Set partitioning in hierarchal trees (SPIHT is a widely used compression algorithm for wavelet transformed images. Among all wavelet transform and zero-tree quantization based image compression algorithms SPIHT has become the benchmark state-of-the-art algorithm because it is simple to implement & yields good results. In this paper we present a comparative study of various wavelet families for image compression with SPIHT algorithm. We have conducted experiments with Daubechies, Coiflet, Symlet, Bi-orthogonal, Reverse Bi-orthogonal and Demeyer wavelet types. The resulting image quality is measured objectively, using peak signal-to-noise ratio (PSNR, and subjectively, using perceived image quality (human visual perception, HVP for short. The resulting reduction in the image size is quantified by compression ratio (CR.

Slow Motion and Zoom in HD Digital Videos Using Fractals

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Maurizio Murroni

2009-01-01

Full Text Available Slow motion replay and spatial zooming are special effects used in digital video rendering. At present, most techniques to perform digital spatial zoom and slow motion are based on interpolation for both enlarging the size of the original pictures and generating additional intermediate frames. Mainly, interpolation is done either by linear or cubic spline functions or by motion estimation/compensation which both can be applied pixel by pixel, or by partitioning frames into blocks. Purpose of this paper is to present an alternative technique combining fractals theory and wavelet decomposition to achieve spatial zoom and slow motion replay of HD digital color video sequences. Fast scene change detection, active scene detection, wavelet subband analysis, and color fractal coding based on Earth Mover's Distance (EMD measure are used to reduce computational load and to improve visual quality. Experiments show that the proposed scheme achieves better results in terms of overall visual quality compared to the state-of-the-art techniques.

WAVELET ANALYSIS OF ABNORMAL ECGS

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Vasudha Nannaparaju

2014-02-01

Full Text Available Detection of the warning signals by the heart can be diagnosed from ECG. An accurate and reliable diagnosis of ECG is very important however which is cumbersome and at times ambiguous in time domain due to the presence of noise. Study of ECG in wavelet domain using both continuous Wavelet transform (CWT and discrete Wavelet transform (DWT, with well known wavelet as well as a wavelet proposed by the authors for this investigation is found to be useful and yields fairly reliable results. In this study, Wavelet analysis of ECGs of Normal, Hypertensive, Diabetic and Cardiac are carried out. The salient feature of the study is that detection of P and T phases in wavelet domain is feasible which are otherwise feeble or absent in raw ECGs.

Fractional Calculus and Shannon Wavelet

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Carlo Cattani

2012-01-01

Full Text Available An explicit analytical formula for the any order fractional derivative of Shannon wavelet is given as wavelet series based on connection coefficients. So that for any 2(ℝ function, reconstructed by Shannon wavelets, we can easily define its fractional derivative. The approximation error is explicitly computed, and the wavelet series is compared with Grünwald fractional derivative by focusing on the many advantages of the wavelet method, in terms of rate of convergence.

Wavelets, vibrations and scalings

CERN Document Server

Meyer, Yves

1997-01-01

Physicists and mathematicians are intensely studying fractal sets of fractal curves. Mandelbrot advocated modeling of real-life signals by fractal or multifractal functions. One example is fractional Brownian motion, where large-scale behavior is related to a corresponding infrared divergence. Self-similarities and scaling laws play a key role in this new area. There is a widely accepted belief that wavelet analysis should provide the best available tool to unveil such scaling laws. And orthonormal wavelet bases are the only existing bases which are structurally invariant through dyadic dilations. This book discusses the relevance of wavelet analysis to problems in which self-similarities are important. Among the conclusions drawn are the following: 1) A weak form of self-similarity can be given a simple characterization through size estimates on wavelet coefficients, and 2) Wavelet bases can be tuned in order to provide a sharper characterization of this self-similarity. A pioneer of the wavelet "saga", Meye...

Improved Side Information Generation for Distributed Video Coding by Exploiting Spatial and Temporal Correlations

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Ye Shuiming

2009-01-01

Full Text Available Distributed video coding (DVC is a video coding paradigm allowing low complexity encoding for emerging applications such as wireless video surveillance. Side information (SI generation is a key function in the DVC decoder, and plays a key-role in determining the performance of the codec. This paper proposes an improved SI generation for DVC, which exploits both spatial and temporal correlations in the sequences. Partially decoded Wyner-Ziv (WZ frames, based on initial SI by motion compensated temporal interpolation, are exploited to improve the performance of the whole SI generation. More specifically, an enhanced temporal frame interpolation is proposed, including motion vector refinement and smoothing, optimal compensation mode selection, and a new matching criterion for motion estimation. The improved SI technique is also applied to a new hybrid spatial and temporal error concealment scheme to conceal errors in WZ frames. Simulation results show that the proposed scheme can achieve up to 1.0 dB improvement in rate distortion performance in WZ frames for video with high motion, when compared to state-of-the-art DVC. In addition, both the objective and perceptual qualities of the corrupted sequences are significantly improved by the proposed hybrid error concealment scheme, outperforming both spatial and temporal concealments alone.

Real-Time Transmission and Storage of Video, Audio, and Health Data in Emergency and Home Care Situations

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Riccardo Stagnaro

2007-01-01

Full Text Available The increase in the availability of bandwidth for wireless links, network integration, and the computational power on fixed and mobile platforms at affordable costs allows nowadays for the handling of audio and video data, their quality making them suitable for medical application. These information streams can support both continuous monitoring and emergency situations. According to this scenario, the authors have developed and implemented the mobile communication system which is described in this paper. The system is based on ITU-T H.323 multimedia terminal recommendation, suitable for real-time data/video/audio and telemedical applications. The audio and video codecs, respectively, H.264 and G723.1, were implemented and optimized in order to obtain high performance on the system target processors. Offline media streaming storage and retrieval functionalities were supported by integrating a relational database in the hospital central system. The system is based on low-cost consumer technologies such as general packet radio service (GPRS and wireless local area network (WLAN or WiFi for lowband data/video transmission. Implementation and testing were carried out for medical emergency and telemedicine application. In this paper, the emergency case study is described.

On transform coding tools under development for VP10

Science.gov (United States)

Parker, Sarah; Chen, Yue; Han, Jingning; Liu, Zoe; Mukherjee, Debargha; Su, Hui; Wang, Yongzhe; Bankoski, Jim; Li, Shunyao

2016-09-01

Google started the WebM Project in 2010 to develop open source, royaltyfree video codecs designed specifically for media on the Web. The second generation codec released by the WebM project, VP9, is currently served by YouTube, and enjoys billions of views per day. Realizing the need for even greater compression efficiency to cope with the growing demand for video on the web, the WebM team embarked on an ambitious project to develop a next edition codec, VP10, that achieves at least a generational improvement in coding efficiency over VP9. Starting from VP9, a set of new experimental coding tools have already been added to VP10 to achieve decent coding gains. Subsequently, Google joined a consortium of major tech companies called the Alliance for Open Media to jointly develop a new codec AV1. As a result, the VP10 effort is largely expected to merge with AV1. In this paper, we focus primarily on new tools in VP10 that improve coding of the prediction residue using transform coding techniques. Specifically, we describe tools that increase the flexibility of available transforms, allowing the codec to handle a more diverse range or residue structures. Results are presented on a standard test set.

Comparison of Video Steganography Methods for Watermark Embedding

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Griberman David

2016-05-01

Full Text Available The paper focuses on the comparison of video steganography methods for the purpose of digital watermarking in the context of copyright protection. Four embedding methods that use Discrete Cosine and Discrete Wavelet Transforms have been researched and compared based on their embedding efficiency and fidelity. A video steganography program has been developed in the Java programming language with all of the researched methods implemented for experiments. The experiments used 3 video containers with different amounts of movement. The impact of the movement has been addressed in the paper as well as the ways of potential improvement of embedding efficiency using adaptive embedding based on the movement amount. Results of the research have been verified using a survey with 17 participants.

Sub-band/transform compression of video sequences

Science.gov (United States)

Sauer, Ken; Bauer, Peter

1992-01-01

The progress on compression of video sequences is discussed. The overall goal of the research was the development of data compression algorithms for high-definition television (HDTV) sequences, but most of our research is general enough to be applicable to much more general problems. We have concentrated on coding algorithms based on both sub-band and transform approaches. Two very fundamental issues arise in designing a sub-band coder. First, the form of the signal decomposition must be chosen to yield band-pass images with characteristics favorable to efficient coding. A second basic consideration, whether coding is to be done in two or three dimensions, is the form of the coders to be applied to each sub-band. Computational simplicity is of essence. We review the first portion of the year, during which we improved and extended some of the previous grant period's results. The pyramid nonrectangular sub-band coder limited to intra-frame application is discussed. Perhaps the most critical component of the sub-band structure is the design of bandsplitting filters. We apply very simple recursive filters, which operate at alternating levels on rectangularly sampled, and quincunx sampled images. We will also cover the techniques we have studied for the coding of the resulting bandpass signals. We discuss adaptive three-dimensional coding which takes advantage of the detection algorithm developed last year. To this point, all the work on this project has been done without the benefit of motion compensation (MC). Motion compensation is included in many proposed codecs, but adds significant computational burden and hardware expense. We have sought to find a lower-cost alternative featuring a simple adaptation to motion in the form of the codec. In sequences of high spatial detail and zooming or panning, it appears that MC will likely be necessary for the proposed quality and bit rates.

Wavelets in physics

CERN Document Server

Fang, Li-Zhi

1998-01-01

Recent advances have shown wavelets to be an effective, and even necessary, mathematical tool for theoretical physics. This book is a timely overview of the progress of this new frontier. It includes an introduction to wavelet analysis, and applications in the fields of high energy physics, astrophysics, cosmology and statistical physics. The topics are selected for the interests of physicists and graduate students of theoretical studies. It emphasizes the need for wavelets in describing and revealing structure in physical problems, which is not easily accomplishing by other methods.

Application of wavelet transform to seismic data; Wavelet henkan no jishin tansa eno tekiyo

Energy Technology Data Exchange (ETDEWEB)

Nakagami, K; Murayama, R; Matsuoka, T [Japan National Oil Corp., Tokyo (Japan)

1996-05-01

Introduced herein is the use of the wavelet transform in the field of seismic exploration. Among applications so far made, there are signal filtering, break point detection, data compression, and the solution of finite differential equations in the wavelet domain. In the field of data compression in particular, some examples of practical application have been introduced already. In seismic exploration, it is expected that the wavelet transform will separate signals and noises in data in a way different from the Fourier transform. The continuous wavelet transform displays time change in frequency easy to read, but is not suitable for the analysis and processing large quantities of data. On the other hand, the discrete wavelet transform, being an orthogonal transform, can handle large quantities of data. As compared with the conventional Fourier transform that handles only the frequency domain, the wavelet transform handles the time domain as well as the frequency domain, and therefore is more convenient in handling unsteady signals. 9 ref., 8 figs.

Scalable Video Coding with Interlayer Signal Decorrelation Techniques

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Yang Wenxian

2007-01-01

Full Text Available Scalability is one of the essential requirements in the compression of visual data for present-day multimedia communications and storage. The basic building block for providing the spatial scalability in the scalable video coding (SVC standard is the well-known Laplacian pyramid (LP. An LP achieves the multiscale representation of the video as a base-layer signal at lower resolution together with several enhancement-layer signals at successive higher resolutions. In this paper, we propose to improve the coding performance of the enhancement layers through efficient interlayer decorrelation techniques. We first show that, with nonbiorthogonal upsampling and downsampling filters, the base layer and the enhancement layers are correlated. We investigate two structures to reduce this correlation. The first structure updates the base-layer signal by subtracting from it the low-frequency component of the enhancement layer signal. The second structure modifies the prediction in order that the low-frequency component in the new enhancement layer is diminished. The second structure is integrated in the JSVM 4.0 codec with suitable modifications in the prediction modes. Experimental results with some standard test sequences demonstrate coding gains up to 1 dB for I pictures and up to 0.7 dB for both I and P pictures.

Wavelets in functional data analysis

CERN Document Server

Morettin, Pedro A; Vidakovic, Brani

2017-01-01

Wavelet-based procedures are key in many areas of statistics, applied mathematics, engineering, and science. This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data. Starting with the Haar wavelet, the authors explore myriad families of wavelets and how they can be used. High-dimensional data visualization (using Andrews' plots), wavelet shrinkage (a simple, yet powerful, procedure for nonparametric models) and a selection of estimation and testing techniques (including a discussion on Stein’s Paradox) make this a highly valuable resource for graduate students and experienced researchers alike.

Signal Analysis by New Mother Wavelets

International Nuclear Information System (INIS)

Niu Jinbo; Qi Kaiguo; Fan Hongyi

2009-01-01

Based on the general formula for finding qualified mother wavelets [Opt. Lett. 31 (2006) 407] we make wavelet transforms computed with the newly found mother wavelets (characteristic of the power 2n) for some optical Gaussian pulses, which exhibit the ability to measure frequency of the pulse more precisely and clearly. We also work with complex mother wavelets composed of new real mother wavelets, which offer the ability of obtaining phase information of the pulse as well as amplitude information. The analogy between the behavior of Hermite-Gauss beams and that of new wavelet transforms is noticed. (general)

A Search Complexity Improvement of Vector Quantization to Immittance Spectral Frequency Coefficients in AMR-WB Speech Codec

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Bing-Jhih Yao

2016-09-01

Full Text Available An adaptive multi-rate wideband (AMR-WB code is a speech codec developed on the basis of an algebraic code-excited linear-prediction (ACELP coding technique, and has a double advantage of low bit rates and high speech quality. This coding technique is widely used in modern mobile communication systems for a high speech quality in handheld devices. However, a major disadvantage is that a vector quantization (VQ of immittance spectral frequency (ISF coefficients occupies a significant computational load in the AMR-WB encoder. Hence, this paper presents a triangular inequality elimination (TIE algorithm combined with a dynamic mechanism and an intersection mechanism, abbreviated as the DI-TIE algorithm, to remarkably improve the complexity of ISF coefficient quantization in the AMR-WB speech codec. Both mechanisms are designed in a way that recursively enhances the performance of the TIE algorithm. At the end of this work, this proposal is experimentally validated as a superior search algorithm relative to a conventional TIE, a multiple TIE (MTIE, and an equal-average equal-variance equal-norm nearest neighbor search (EEENNS approach. With a full search algorithm as a benchmark for search load comparison, this work provides a search load reduction above 77%, a figure far beyond 36% in the TIE, 49% in the MTIE, and 68% in the EEENNS approach.

A new approach to pre-processing digital image for wavelet-based watermark

Science.gov (United States)

Agreste, Santa; Andaloro, Guido

2008-11-01

The growth of the Internet has increased the phenomenon of digital piracy, in multimedia objects, like software, image, video, audio and text. Therefore it is strategic to individualize and to develop methods and numerical algorithms, which are stable and have low computational cost, that will allow us to find a solution to these problems. We describe a digital watermarking algorithm for color image protection and authenticity: robust, not blind, and wavelet-based. The use of Discrete Wavelet Transform is motivated by good time-frequency features and a good match with Human Visual System directives. These two combined elements are important for building an invisible and robust watermark. Moreover our algorithm can work with any image, thanks to the step of pre-processing of the image that includes resize techniques that adapt to the size of the original image for Wavelet transform. The watermark signal is calculated in correlation with the image features and statistic properties. In the detection step we apply a re-synchronization between the original and watermarked image according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has been shown to be resistant against geometric, filtering, and StirMark attacks with a low rate of false alarm.

FY 1998 results of the regional consortium R and D project/the venture promotion type regional consortium R and D (small-/medium-size venture creation type). 2nd year. R and D of the audiovisual coding/decoding technology in the low bit-rate mutltimedia communication system; 1998 nendo tei bit rate multimedia tsushinkei ni okeru gazo onsei fugo fukugoka gijutsu no kenkyu kaihatsu seika hokokusho. 2

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-03-01

The paper studied how to solve the problems in TV telephones such as low quality of pictures and less application. As to the development of H.263 codec LSI, an architecture which makes the efficient moving image codec possible even at low action frequency was designed for achieving low electric power consumption, and the LSI was mounted. In relation to the development of G.723.1 codec soft on SH3, encoding motion was conducted with audio data inputted, and it was confirmed that the bit stream obtained was effective. For the verification of motion/system of ASIC, conducted were the design/development of the reference board for mobile information devices and the verification using the board. The one that is correspondent to the low bit-rate for development is 1485 macroblock/second in the required performance in MPEG-4, and it was confirmed that it could be fully achieved even by the designed H.263 core. Concerning the object processing, an object extraction algorithm was devised. An algorithm of the moving picture codec was designed by conversion of discrete wavelets which were reduced in memory use amount. (NEDO)

Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals

Directory of Open Access Journals (Sweden)

Jikai Chen

2016-12-01

Full Text Available In a power system, the analysis of transient signals is the theoretical basis of fault diagnosis and transient protection theory. Shannon wavelet entropy (SWE and Shannon wavelet packet entropy (SWPE are powerful mathematics tools for transient signal analysis. Combined with the recent achievements regarding SWE and SWPE, their applications are summarized in feature extraction of transient signals and transient fault recognition. For wavelet aliasing at adjacent scale of wavelet decomposition, the impact of wavelet aliasing is analyzed for feature extraction accuracy of SWE and SWPE, and their differences are compared. Meanwhile, the analyses mentioned are verified by partial discharge (PD feature extraction of power cable. Finally, some new ideas and further researches are proposed in the wavelet entropy mechanism, operation speed and how to overcome wavelet aliasing.

Information Hiding In Digital Video Using DCT, DWT and CvT

Science.gov (United States)

Abed Shukur, Wisam; Najah Abdullah, Wathiq; Kareem Qurban, Luheb

2018-05-01

The type of video that used in this proposed hiding a secret information technique is .AVI; the proposed technique of a data hiding to embed a secret information into video frames by using Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Curvelet Transform (CvT). An individual pixel consists of three color components (RGB), the secret information is embedded in Red (R) color channel. On the receiver side, the secret information is extracted from received video. After extracting secret information, robustness of proposed hiding a secret information technique is measured and obtained by computing the degradation of the extracted secret information by comparing it with the original secret information via calculating the Normalized cross Correlation (NC). The experiments shows the error ratio of the proposed technique is (8%) while accuracy ratio is (92%) when the Curvelet Transform (CvT) is used, but compared with Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT), the error rates are 11% and 14% respectively, while the accuracy ratios are (89%) and (86%) respectively. So, the experiments shows the Poisson noise gives better results than other types of noises, while the speckle noise gives worst results compared with other types of noises. The proposed technique has been established by using MATLAB R2016a programming language.

An Introduction to Wavelet Theory and Analysis

Energy Technology Data Exchange (ETDEWEB)

Miner, N.E.

1998-10-01

This report reviews the history, theory and mathematics of wavelet analysis. Examination of the Fourier Transform and Short-time Fourier Transform methods provides tiormation about the evolution of the wavelet analysis technique. This overview is intended to provide readers with a basic understanding of wavelet analysis, define common wavelet terminology and describe wavelet amdysis algorithms. The most common algorithms for performing efficient, discrete wavelet transforms for signal analysis and inverse discrete wavelet transforms for signal reconstruction are presented. This report is intended to be approachable by non- mathematicians, although a basic understanding of engineering mathematics is necessary.

A wavelet phase filter for emission tomography

International Nuclear Information System (INIS)

Olsen, E.T.; Lin, B.

1995-01-01

The presence of a high level of noise is a characteristic in some tomographic imaging techniques such as positron emission tomography (PET). Wavelet methods can smooth out noise while preserving significant features of images. Mallat et al. proposed a wavelet based denoising scheme exploiting wavelet modulus maxima, but the scheme is sensitive to noise. In this study, the authors explore the properties of wavelet phase, with a focus on reconstruction of emission tomography images. Specifically, they show that the wavelet phase of regular Poisson noise under a Haar-type wavelet transform converges in distribution to a random variable uniformly distributed on [0, 2π). They then propose three wavelet-phase-based denoising schemes which exploit this property: edge tracking, local phase variance thresholding, and scale phase variation thresholding. Some numerical results are also presented. The numerical experiments indicate that wavelet phase techniques show promise for wavelet based denoising methods

Wavelets y sus aplicaciones

OpenAIRE

Castro, Liliana Raquel; Castro, Silvia Mabel

1995-01-01

Se presenta una introducción a la teorfa de wavelets. Ademas, se da una revisión histórica de cómo fueron introducidas las wavelets para la representación de funciones. Se efectúa una comparación entre la transformada wavelet y la transformada de Fourier. Por último, se presentan también algunas de los múltiples aplicaciones de esta nueva herramienta de análisis armónico.

Fuzzy Logic Control of Adaptive ARQ for Video Distribution over a Bluetooth Wireless Link

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R. Razavi

2007-01-01

Full Text Available Bluetooth's default automatic repeat request (ARQ scheme is not suited to video distribution resulting in missed display and decoded deadlines. Adaptive ARQ with active discard of expired packets from the send buffer is an alternative approach. However, even with the addition of cross-layer adaptation to picture-type packet importance, ARQ is not ideal in conditions of a deteriorating RF channel. The paper presents fuzzy logic control of ARQ, based on send buffer fullness and the head-of-line packet's deadline. The advantage of the fuzzy logic approach, which also scales its output according to picture type importance, is that the impact of delay can be directly introduced to the model, causing retransmissions to be reduced compared to all other schemes. The scheme considers both the delay constraints of the video stream and at the same time avoids send buffer overflow. Tests explore a variety of Bluetooth send buffer sizes and channel conditions. For adverse channel conditions and buffer size, the tests show an improvement of at least 4 dB in video quality compared to nonfuzzy schemes. The scheme can be applied to any codec with I-, P-, and (possibly B-slices by inspection of packet headers without the need for encoder intervention.

Target recognition by wavelet transform

International Nuclear Information System (INIS)

Li Zhengdong; He Wuliang; Zheng Xiaodong; Cheng Jiayuan; Peng Wen; Pei Chunlan; Song Chen

2002-01-01

Wavelet transform has an important character of multi-resolution power, which presents pyramid structure, and this character coincides the way by which people distinguish object from coarse to fineness and from large to tiny. In addition to it, wavelet transform benefits to reducing image noise, simplifying calculation, and embodying target image characteristic point. A method of target recognition by wavelet transform is provided

Wavelet frames and their duals

DEFF Research Database (Denmark)

Lemvig, Jakob

2008-01-01

frames with good time localization and other attractive properties. Furthermore, the dual wavelet frames are constructed in such a way that we are guaranteed that both frames will have the same desirable features. The construction procedure works for any real, expansive dilation. A quasi-affine system....... The signals are then represented by linear combinations of the building blocks with coefficients found by an associated frame, called a dual frame. A wavelet frame is a frame where the building blocks are stretched (dilated) and translated versions of a single function; such a frame is said to have wavelet...... structure. The dilation of the wavelet building blocks in higher dimension is done via a square matrix which is usually taken to be integer valued. In this thesis we step away from the "usual" integer, expansive dilation and consider more general, expansive dilations. In most applications of wavelet frames...

Wavelet-based moment invariants for pattern recognition

Science.gov (United States)

Chen, Guangyi; Xie, Wenfang

2011-07-01

Moment invariants have received a lot of attention as features for identification and inspection of two-dimensional shapes. In this paper, two sets of novel moments are proposed by using the auto-correlation of wavelet functions and the dual-tree complex wavelet functions. It is well known that the wavelet transform lacks the property of shift invariance. A little shift in the input signal will cause very different output wavelet coefficients. The autocorrelation of wavelet functions and the dual-tree complex wavelet functions, on the other hand, are shift-invariant, which is very important in pattern recognition. Rotation invariance is the major concern in this paper, while translation invariance and scale invariance can be achieved by standard normalization techniques. The Gaussian white noise is added to the noise-free images and the noise levels vary with different signal-to-noise ratios. Experimental results conducted in this paper show that the proposed wavelet-based moments outperform Zernike's moments and the Fourier-wavelet descriptor for pattern recognition under different rotation angles and different noise levels. It can be seen that the proposed wavelet-based moments can do an excellent job even when the noise levels are very high.

Cross-Layer Measurement on an IEEE 802.11g Wireless Network Supporting MPEG-2 Video Streaming Applications in the Presence of Interference

Directory of Open Access Journals (Sweden)

Alessandro Sona

2010-01-01

Full Text Available The performance of wireless local area networks supporting video streaming applications, based on MPEG-2 video codec, in the presence of interference is here dealt with. IEEE 802.11g standard wireless networks, that do not support QoS in according with IEEE 802.11e standard, are, in particular, accounted for and Bluetooth signals, additive white Gaussian noise, and competitive data traffic are considered as sources of interference. The goal is twofold: from one side, experimentally assessing and correlating the values that some performance metrics assume at the same time at different layers of an IEEE 802.11g WLAN delivering video streaming in the presence of in-channel interference; from the other side, deducing helpful and practical hints for designers and technicians, in order to efficiently assess and enhance the performance of an IEEE 802.11g WLAN supporting video streaming in some suitable setup conditions and in the presence of interference. To this purpose, an experimental analysis is planned following a cross-layer measurement approach, and a proper testbed within a semianechoic chamber is used. Valuable results are obtained in terms of signal-to-interference ratio, packet loss ratio, jitter, video quality, and interference data rate; helpful hints for designers and technicians are finally gained.

Wavelet entropy characterization of elevated intracranial pressure.

Science.gov (United States)

Xu, Peng; Scalzo, Fabien; Bergsneider, Marvin; Vespa, Paul; Chad, Miller; Hu, Xiao

2008-01-01

Intracranial Hypertension (ICH) often occurs for those patients with traumatic brain injury (TBI), stroke, tumor, etc. Pathology of ICH is still controversial. In this work, we used wavelet entropy and relative wavelet entropy to study the difference existed between normal and hypertension states of ICP for the first time. The wavelet entropy revealed the similar findings as the approximation entropy that entropy during ICH state is smaller than that in normal state. Moreover, with wavelet entropy, we can see that ICH state has the more focused energy in the low wavelet frequency band (0-3.1 Hz) than the normal state. The relative wavelet entropy shows that the energy distribution in the wavelet bands between these two states is actually different. Based on these results, we suggest that ICH may be formed by the re-allocation of oscillation energy within brain.

A generalized wavelet extrema representation

Energy Technology Data Exchange (ETDEWEB)

Lu, Jian; Lades, M.

1995-10-01

The wavelet extrema representation originated by Stephane Mallat is a unique framework for low-level and intermediate-level (feature) processing. In this paper, we present a new form of wavelet extrema representation generalizing Mallat`s original work. The generalized wavelet extrema representation is a feature-based multiscale representation. For a particular choice of wavelet, our scheme can be interpreted as representing a signal or image by its edges, and peaks and valleys at multiple scales. Such a representation is shown to be stable -- the original signal or image can be reconstructed with very good quality. It is further shown that a signal or image can be modeled as piecewise monotonic, with all turning points between monotonic segments given by the wavelet extrema. A new projection operator is introduced to enforce piecewise inonotonicity of a signal in its reconstruction. This leads to an enhancement to previously developed algorithms in preventing artifacts in reconstructed signal.

Wavelet theory and its applications

Energy Technology Data Exchange (ETDEWEB)

Faber, V.; Bradley, JJ.; Brislawn, C.; Dougherty, R.; Hawrylycz, M.

1996-07-01

This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). We investigated the theory of wavelet transforms and their relation to Laboratory applications. The investigators have had considerable success in the past applying wavelet techniques to the numerical solution of optimal control problems for distributed- parameter systems, nonlinear signal estimation, and compression of digital imagery and multidimensional data. Wavelet theory involves ideas from the fields of harmonic analysis, numerical linear algebra, digital signal processing, approximation theory, and numerical analysis, and the new computational tools arising from wavelet theory are proving to be ideal for many Laboratory applications. 10 refs.

Segment scheduling method for reducing 360° video streaming latency

Science.gov (United States)

Gudumasu, Srinivas; Asbun, Eduardo; He, Yong; Ye, Yan

2017-09-01

360° video is an emerging new format in the media industry enabled by the growing availability of virtual reality devices. It provides the viewer a new sense of presence and immersion. Compared to conventional rectilinear video (2D or 3D), 360° video poses a new and difficult set of engineering challenges on video processing and delivery. Enabling comfortable and immersive user experience requires very high video quality and very low latency, while the large video file size poses a challenge to delivering 360° video in a quality manner at scale. Conventionally, 360° video represented in equirectangular or other projection formats can be encoded as a single standards-compliant bitstream using existing video codecs such as H.264/AVC or H.265/HEVC. Such method usually needs very high bandwidth to provide an immersive user experience. While at the client side, much of such high bandwidth and the computational power used to decode the video are wasted because the user only watches a small portion (i.e., viewport) of the entire picture. Viewport dependent 360°video processing and delivery approaches spend more bandwidth on the viewport than on non-viewports and are therefore able to reduce the overall transmission bandwidth. This paper proposes a dual buffer segment scheduling algorithm for viewport adaptive streaming methods to reduce latency when switching between high quality viewports in 360° video streaming. The approach decouples the scheduling of viewport segments and non-viewport segments to ensure the viewport segment requested matches the latest user head orientation. A base layer buffer stores all lower quality segments, and a viewport buffer stores high quality viewport segments corresponding to the most recent viewer's head orientation. The scheduling scheme determines viewport requesting time based on the buffer status and the head orientation. This paper also discusses how to deploy the proposed scheduling design for various viewport adaptive video

Unsupervised symmetrical trademark image retrieval in soccer telecast using wavelet energy and quadtree decomposition

Science.gov (United States)

Ong, Swee Khai; Lim, Wee Keong; Soo, Wooi King

2013-04-01

Trademark, a distinctive symbol, is used to distinguish products or services provided by a particular person, group or organization from other similar entries. As trademark represents the reputation and credit standing of the owner, it is important to differentiate one trademark from another. Many methods have been proposed to identify, classify and retrieve trademarks. However, most methods required features database and sample sets for training prior to recognition and retrieval process. In this paper, a new feature on wavelet coefficients, the localized wavelet energy, is introduced to extract features of trademarks. With this, unsupervised content-based symmetrical trademark image retrieval is proposed without the database and prior training set. The feature analysis is done by an integration of the proposed localized wavelet energy and quadtree decomposed regional symmetrical vector. The proposed framework eradicates the dependence on query database and human participation during the retrieval process. In this paper, trademarks for soccer games sponsors are the intended trademark category. Video frames from soccer telecast are extracted and processed for this study. Reasonably good localization and retrieval results on certain categories of trademarks are achieved. A distinctive symbol is used to distinguish products or services provided by a particular person, group or organization from other similar entries.

Construction of wavelets with composite dilations

International Nuclear Information System (INIS)

Wu Guochang; Li Zhiqiang; Cheng Zhengxing

2009-01-01

In order to overcome classical wavelets' shortcoming in image processing problems, people developed many producing systems, which built up wavelet family. In this paper, the notion of AB-multiresolution analysis is generalized, and the corresponding theory is developed. For an AB-multiresolution analysis associated with any expanding matrices, we deduce that there exists a singe scaling function in its reducing subspace. Under some conditions, wavelets with composite dilations can be gotten by AB-multiresolution analysis, which permits the existence of fast implementation algorithm. Then, we provide an approach to design the wavelets with composite dilations by classic wavelets. Our way consists of separable and partly nonseparable cases. In each section, we construct all kinds of examples with nice properties to prove our theory.

Wavelets a tutorial in theory and applications

CERN Document Server

1992-01-01

Wavelets: A Tutorial in Theory and Applications is the second volume in the new series WAVELET ANALYSIS AND ITS APPLICATIONS. As a companion to the first volume in this series, this volume covers several of the most important areas in wavelets, ranging from the development of the basic theory such as construction and analysis of wavelet bases to an introduction of some of the key applications, including Mallat's local wavelet maxima technique in second generation image coding. A fairly extensive bibliography is also included in this volume.Key Features* Covers several of the

Boosted bosons and wavelets

CERN Document Server

Søgaard, Andreas

For the LHC Run 2 and beyond, experiments are pushing both the energy and the intensity frontier so the need for robust and efficient pile-up mitigation tools becomes ever more pressing. Several methods exist, relying on uniformity of pile-up, local correlations of charged to neutral particles, and parton shower shapes, all in $y − \\phi$ space. Wavelets are presented as tools for pile-up removal, utilising their ability to encode position and frequency information simultaneously. This allows for the separation of individual hadron collision events by angular scale and thus for subtracting of soft, diffuse/wide-angle contributions while retaining the hard, small-angle components from the hard event. Wavelet methods may utilise the same assumptions as existing methods, the difference being the underlying, novel representation. Several wavelet methods are proposed and their effect studied in simple toy simulation under conditions relevant for the LHC Run 2. One full pile-up mitigation tool (‘wavelet analysis...

Robust video watermarking via optimization algorithm for quantization of pseudo-random semi-global statistics

Science.gov (United States)

Kucukgoz, Mehmet; Harmanci, Oztan; Mihcak, Mehmet K.; Venkatesan, Ramarathnam

2005-03-01

In this paper, we propose a novel semi-blind video watermarking scheme, where we use pseudo-random robust semi-global features of video in the three dimensional wavelet transform domain. We design the watermark sequence via solving an optimization problem, such that the features of the mark-embedded video are the quantized versions of the features of the original video. The exact realizations of the algorithmic parameters are chosen pseudo-randomly via a secure pseudo-random number generator, whose seed is the secret key, that is known (resp. unknown) by the embedder and the receiver (resp. by the public). We experimentally show the robustness of our algorithm against several attacks, such as conventional signal processing modifications and adversarial estimation attacks.

Wavelet transforms as solutions of partial differential equations

Energy Technology Data Exchange (ETDEWEB)

Zweig, G.

1997-10-01

This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Wavelet transforms are useful in representing transients whose time and frequency structure reflect the dynamics of an underlying physical system. Speech sound, pressure in turbulent fluid flow, or engine sound in automobiles are excellent candidates for wavelet analysis. This project focused on (1) methods for choosing the parent wavelet for a continuous wavelet transform in pattern recognition applications and (2) the more efficient computation of continuous wavelet transforms by understanding the relationship between discrete wavelet transforms and discretized continuous wavelet transforms. The most interesting result of this research is the finding that the generalized wave equation, on which the continuous wavelet transform is based, can be used to understand phenomena that relate to the process of hearing.

Wavelet spectra of JACEE events

International Nuclear Information System (INIS)

Suzuki, Naomichi; Biyajima, Minoru; Ohsawa, Akinori.

1995-01-01

Pseudo-rapidity distributions of two high multiplicity events Ca-C and Si-AgBr observed by the JACEE are analyzed by a wavelet transform. Wavelet spectra of those events are calculated and compared with the simulation calculations. The wavelet spectrum of the Ca-C event somewhat resembles that simulated with the uniform random numbers. That of Si-AgBr event, however, is not reproduced by simulation calculations with Poisson random numbers, uniform random numbers, or a p-model. (author)

Digital video technologies and their network requirements

Energy Technology Data Exchange (ETDEWEB)

R. P. Tsang; H. Y. Chen; J. M. Brandt; J. A. Hutchins

1999-11-01

Coded digital video signals are considered to be one of the most difficult data types to transport due to their real-time requirements and high bit rate variability. In this study, the authors discuss the coding mechanisms incorporated by the major compression standards bodies, i.e., JPEG and MPEG, as well as more advanced coding mechanisms such as wavelet and fractal techniques. The relationship between the applications which use these coding schemes and their network requirements are the major focus of this study. Specifically, the authors relate network latency, channel transmission reliability, random access speed, buffering and network bandwidth with the various coding techniques as a function of the applications which use them. Such applications include High-Definition Television, Video Conferencing, Computer-Supported Collaborative Work (CSCW), and Medical Imaging.

Parsimonious Wavelet Kernel Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Wang Qin

2015-11-01

Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.

Wavelet analysis in neurodynamics

International Nuclear Information System (INIS)

Pavlov, Aleksei N; Hramov, Aleksandr E; Koronovskii, Aleksei A; Sitnikova, Evgenija Yu; Makarov, Valeri A; Ovchinnikov, Alexey A

2012-01-01

Results obtained using continuous and discrete wavelet transforms as applied to problems in neurodynamics are reviewed, with the emphasis on the potential of wavelet analysis for decoding signal information from neural systems and networks. The following areas of application are considered: (1) the microscopic dynamics of single cells and intracellular processes, (2) sensory data processing, (3) the group dynamics of neuronal ensembles, and (4) the macrodynamics of rhythmical brain activity (using multichannel EEG recordings). The detection and classification of various oscillatory patterns of brain electrical activity and the development of continuous wavelet-based brain activity monitoring systems are also discussed as possibilities. (reviews of topical problems)

Wavelet-LMS algorithm-based echo cancellers

Science.gov (United States)

Seetharaman, Lalith K.; Rao, Sathyanarayana S.

2002-12-01

This paper presents Echo Cancellers based on the Wavelet-LMS Algorithm. The performance of the Least Mean Square Algorithm in Wavelet transform domain is observed and its application in Echo cancellation is analyzed. The Widrow-Hoff Least Mean Square Algorithm is most widely used algorithm for Adaptive filters that function as Echo Cancellers. The present day communication signals are widely non-stationary in nature and some errors crop up when Least Mean Square Algorithm is used for the Echo Cancellers handling such signals. The analysis of non-stationary signals often involves a compromise between how well transitions or discontinuities can be located. The multi-scale or multi-resolution of signal analysis, which is the essence of wavelet transform, makes Wavelets popular in non-stationary signal analysis. In this paper, we present a Wavelet-LMS algorithm wherein the wavelet coefficients of a signal are modified adaptively using the Least Mean Square Algorithm and then reconstructed to give an Echo-free signal. The Echo Canceller based on this Algorithm is found to have a better convergence and a comparatively lesser MSE (Mean Square error).

Wavelet analysis for nonstationary signals

International Nuclear Information System (INIS)

Penha, Rosani Maria Libardi da

1999-01-01

Mechanical vibration signals play an important role in anomalies identification resulting of equipment malfunctioning. Traditionally, Fourier spectral analysis is used where the signals are assumed to be stationary. However, occasional transient impulses and start-up process are examples of nonstationary signals that can be found in mechanical vibrations. These signals can provide important information about the equipment condition, as early fault detection. The Fourier analysis can not adequately be applied to nonstationary signals because the results provide data about the frequency composition averaged over the duration of the signal. In this work, two methods for nonstationary signal analysis are used: Short Time Fourier Transform (STFT) and wavelet transform. The STFT is a method of adapting Fourier spectral analysis for nonstationary application to time-frequency domain. To have a unique resolution throughout the entire time-frequency domain is its main limitation. The wavelet transform is a new analysis technique suitable to nonstationary signals, which handles the STFT drawbacks, providing multi-resolution frequency analysis and time localization in a unique time-scale graphic. The multiple frequency resolutions are obtained by scaling (dilatation/compression) the wavelet function. A comparison of the conventional Fourier transform, STFT and wavelet transform is made applying these techniques to: simulated signals, arrangement rotor rig vibration signal and rotate machine vibration signal Hanning window was used to STFT analysis. Daubechies and harmonic wavelets were used to continuos, discrete and multi-resolution wavelet analysis. The results show the Fourier analysis was not able to detect changes in the signal frequencies or discontinuities. The STFT analysis detected the changes in the signal frequencies, but with time-frequency resolution problems. The wavelet continuos and discrete transform demonstrated to be a high efficient tool to detect

Analysis of transient signals by Wavelet transform

International Nuclear Information System (INIS)

Penha, Rosani Libardi da; Silva, Aucyone A. da; Ting, Daniel K.S.; Oliveira Neto, Jose Messias de

2000-01-01

The objective of this work is to apply the Wavelet Transform in transient signals. The Wavelet technique can outline the short time events that are not easily detected using traditional techniques. In this work, the Wavelet Transform is compared with Fourier Transform, by using simulated data and rotor rig data. This data contain known transients. The wavelet could follow all the transients, what do not happen to the Fourier techniques. (author)

Wavelets for Sparse Representation of Music

DEFF Research Database (Denmark)

Endelt, Line Ørtoft; Harbo, Anders La-Cour

2004-01-01

We are interested in obtaining a sparse representation of music signals by means of a discrete wavelet transform (DWT). That means we want the energy in the representation to be concentrated in few DWT coefficients. It is well-known that the decay of the DWT coefficients is strongly related...... to the number of vanishing moments of the mother wavelet, and to the smoothness of the signal. In this paper we present the result of applying two classical families of wavelets to a series of musical signals. The purpose is to determine a general relation between the number of vanishing moments of the wavelet...

Wavelet-based prediction of oil prices

International Nuclear Information System (INIS)

Yousefi, Shahriar; Weinreich, Ilona; Reinarz, Dominik

2005-01-01

This paper illustrates an application of wavelets as a possible vehicle for investigating the issue of market efficiency in futures markets for oil. The paper provides a short introduction to the wavelets and a few interesting wavelet-based contributions in economics and finance are briefly reviewed. A wavelet-based prediction procedure is introduced and market data on crude oil is used to provide forecasts over different forecasting horizons. The results are compared with data from futures markets for oil and the relative performance of this procedure is used to investigate whether futures markets are efficiently priced

Wavelets a primer

CERN Document Server

Blatter, Christian

1998-01-01

The Wavelet Transform has stimulated research that is unparalleled since the invention of the Fast Fourier Transform and has opened new avenues of applications in signal processing, image compression, radiology, cardiology, and many other areas. This book grew out of a short course for mathematics students at the ETH in Zurich; it provides a solid mathematical foundation for the broad range of applications enjoyed by the wavelet transform. Numerous illustrations and fully worked out examples enhance the book.

Wavelet-based study of valence-arousal model of emotions on EEG signals with LabVIEW.

Science.gov (United States)

Guzel Aydin, Seda; Kaya, Turgay; Guler, Hasan

2016-06-01

This paper illustrates the wavelet-based feature extraction for emotion assessment using electroencephalogram (EEG) signal through graphical coding design. Two-dimensional (valence-arousal) emotion model was studied. Different emotions (happy, joy, melancholy, and disgust) were studied for assessment. These emotions were stimulated by video clips. EEG signals obtained from four subjects were decomposed into five frequency bands (gamma, beta, alpha, theta, and delta) using "db5" wavelet function. Relative features were calculated to obtain further information. Impact of the emotions according to valence value was observed to be optimal on power spectral density of gamma band. The main objective of this work is not only to investigate the influence of the emotions on different frequency bands but also to overcome the difficulties in the text-based program. This work offers an alternative approach for emotion evaluation through EEG processing. There are a number of methods for emotion recognition such as wavelet transform-based, Fourier transform-based, and Hilbert-Huang transform-based methods. However, the majority of these methods have been applied with the text-based programming languages. In this study, we proposed and implemented an experimental feature extraction with graphics-based language, which provides great convenience in bioelectrical signal processing.

Comparison between wavelet and wavelet packet transform features for classification of faults in distribution system

Science.gov (United States)

Arvind, Pratul

2012-11-01

The ability to identify and classify all ten types of faults in a distribution system is an important task for protection engineers. Unlike transmission system, distribution systems have a complex configuration and are subjected to frequent faults. In the present work, an algorithm has been developed for identifying all ten types of faults in a distribution system by collecting current samples at the substation end. The samples are subjected to wavelet packet transform and artificial neural network in order to yield better classification results. A comparison of results between wavelet transform and wavelet packet transform is also presented thereby justifying the feature extracted from wavelet packet transform yields promising results. It should also be noted that current samples are collected after simulating a 25kv distribution system in PSCAD software.

Direct migration motion estimation and mode decision to decoder for a low-complexity decoder Wyner-Ziv video coding

Science.gov (United States)

Lei, Ted Chih-Wei; Tseng, Fan-Shuo

2017-07-01

This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.

A wavelet ridge extraction method employing a novel cost function in two-dimensional wavelet transform profilometry

Science.gov (United States)

Wang, Jianhua; Yang, Yanxi

2018-05-01

We present a new wavelet ridge extraction method employing a novel cost function in two-dimensional wavelet transform profilometry (2-D WTP). First of all, the maximum value point is extracted from two-dimensional wavelet transform coefficient modulus, and the local extreme value points over 90% of maximum value are also obtained, they both constitute wavelet ridge candidates. Then, the gradient of rotate factor is introduced into the Abid's cost function, and the logarithmic Logistic model is used to adjust and improve the cost function weights so as to obtain more reasonable value estimation. At last, the dynamic programming method is used to accurately find the optimal wavelet ridge, and the wrapped phase can be obtained by extracting the phase at the ridge. Its advantage is that, the fringe pattern with low signal-to-noise ratio can be demodulated accurately, and its noise immunity will be better. Meanwhile, only one fringe pattern is needed to projected to measured object, so dynamic three-dimensional (3-D) measurement in harsh environment can be realized. Computer simulation and experimental results show that, for the fringe pattern with noise pollution, the 3-D surface recovery accuracy by the proposed algorithm is increased. In addition, the demodulation phase accuracy of Morlet, Fan and Cauchy mother wavelets are compared.

Some applications of wavelets to physics

International Nuclear Information System (INIS)

Thompson, C.R.

1992-01-01

A thorough description of a fast wavelet transform algorithm (FWT) and its inverse (IFWT) are given. The effects of noise in the wavelet transform are studied, in particular the effects on signal reconstruction. A model for additive white noise on the coefficients is presented along with two methods that can help to suppress the effects of noise corruption of the signal. Problems of improper sampling are studied, including the propagation of uncertainty through the FWT and IFWT. Interpolation techniques and data compression are also studied. The FWT and IFWT are generalized for analysis of two dimensional images. Methods for edge detection are discussed as well as contrast improvement and data compression. Finally, wavelets are applied to electromagnetic wave propagation problems. Formulas relating the wavelet and Fourier transforms are given, and expansions of time-dependent electromagnetic fields using both fixed and moving wavelet bases are studied

Cross wavelet analysis: significance testing and pitfalls

Directory of Open Access Journals (Sweden)

D. Maraun

2004-01-01

Full Text Available In this paper, we present a detailed evaluation of cross wavelet analysis of bivariate time series. We develop a statistical test for zero wavelet coherency based on Monte Carlo simulations. If at least one of the two processes considered is Gaussian white noise, an approximative formula for the critical value can be utilized. In a second part, typical pitfalls of wavelet cross spectra and wavelet coherency are discussed. The wavelet cross spectrum appears to be not suitable for significance testing the interrelation between two processes. Instead, one should rather apply wavelet coherency. Furthermore we investigate problems due to multiple testing. Based on these results, we show that coherency between ENSO and NAO is an artefact for most of the time from 1900 to 1995. However, during a distinct period from around 1920 to 1940, significant coherency between the two phenomena occurs.

From Fourier analysis to wavelets

CERN Document Server

Gomes, Jonas

2015-01-01

This text introduces the basic concepts of function spaces and operators, both from the continuous and discrete viewpoints.  Fourier and Window Fourier Transforms are introduced and used as a guide to arrive at the concept of Wavelet transform.  The fundamental aspects of multiresolution representation, and its importance to function discretization and to the construction of wavelets is also discussed. Emphasis is given on ideas and intuition, avoiding the heavy computations which are usually involved in the study of wavelets.  Readers should have a basic knowledge of linear algebra, calculus, and some familiarity with complex analysis.  Basic knowledge of signal and image processing is desirable. This text originated from a set of notes in Portuguese that the authors wrote for a wavelet course on the Brazilian Mathematical Colloquium in 1997 at IMPA, Rio de Janeiro.

Wavelet based free-form deformations for nonrigid registration

Science.gov (United States)

Sun, Wei; Niessen, Wiro J.; Klein, Stefan

2014-03-01

In nonrigid registration, deformations may take place on the coarse and fine scales. For the conventional B-splines based free-form deformation (FFD) registration, these coarse- and fine-scale deformations are all represented by basis functions of a single scale. Meanwhile, wavelets have been proposed as a signal representation suitable for multi-scale problems. Wavelet analysis leads to a unique decomposition of a signal into its coarse- and fine-scale components. Potentially, this could therefore be useful for image registration. In this work, we investigate whether a wavelet-based FFD model has advantages for nonrigid image registration. We use a B-splines based wavelet, as defined by Cai and Wang.1 This wavelet is expressed as a linear combination of B-spline basis functions. Derived from the original B-spline function, this wavelet is smooth, differentiable, and compactly supported. The basis functions of this wavelet are orthogonal across scales in Sobolev space. This wavelet was previously used for registration in computer vision, in 2D optical flow problems,2 but it was not compared with the conventional B-spline FFD in medical image registration problems. An advantage of choosing this B-splines based wavelet model is that the space of allowable deformation is exactly equivalent to that of the traditional B-spline. The wavelet transformation is essentially a (linear) reparameterization of the B-spline transformation model. Experiments on 10 CT lung and 18 T1-weighted MRI brain datasets show that wavelet based registration leads to smoother deformation fields than traditional B-splines based registration, while achieving better accuracy.

Wavelet Radiosity on Arbitrary Planar Surfaces

OpenAIRE

Holzschuch , Nicolas; Cuny , François; Alonso , Laurent

2000-01-01

Colloque avec actes et comité de lecture. internationale.; International audience; Wavelet radiosity is, by its nature, restricted to parallelograms or triangles. This paper presents an innovative technique enabling wavelet radiosity computations on planar surfaces of arbitrary shape, including concave contours or contours with holes. This technique replaces the need for triangulating such complicated shapes, greatly reducing the complexity of the wavelet radiosity algorithm and the computati...

Optical Aperture Synthesis Object's Information Extracting Based on Wavelet Denoising

International Nuclear Information System (INIS)

Fan, W J; Lu, Y

2006-01-01

Wavelet denoising is studied to improve OAS(optical aperture synthesis) object's Fourier information extracting. Translation invariance wavelet denoising based on Donoho wavelet soft threshold denoising is researched to remove Pseudo-Gibbs in wavelet soft threshold image. OAS object's information extracting based on translation invariance wavelet denoising is studied. The study shows that wavelet threshold denoising can improve the precision and the repetition of object's information extracting from interferogram, and the translation invariance wavelet denoising information extracting is better than soft threshold wavelet denoising information extracting

Comparison on Integer Wavelet Transforms in Spherical Wavelet Based Image Based Relighting

Institute of Scientific and Technical Information of China (English)

WANGZe; LEEYin; LEUNGChising; WONGTientsin; ZHUYisheng

2003-01-01

To provide a good quality rendering in the Image based relighting (IBL) system, tremendous reference images under various illumination conditions are needed. Therefore data compression is essential to enable interactive action. And the rendering speed is another crucial consideration for real applications. Based on Spherical wavelet transform (SWT), this paper presents a quick representation method with Integer wavelet transform (IWT) for the IBL system. It focuses on comparison on different IWTs with the Embedded zerotree wavelet (EZW) used in the IBL system. The whole compression procedure contains two major compression steps. Firstly, SWT is applied to consider the correlation among different reference images. Secondly, the SW transformed images are compressed with IWT based image compression approach. Two IWTs are used and good results are showed in the simulations.

Visualization of a Turbulent Jet Using Wavelets

Institute of Scientific and Technical Information of China (English)

Hui LI

2001-01-01

An application of multiresolution image analysis to turbulence was investigated in this paper, in order to visualize the coherent structure and the most essential scales governing turbulence. The digital imaging photograph of jet slice was decomposed by two-dimensional discrete wavelet transform based on Daubechies, Coifman and Baylkin bases. The best choice of orthogonal wavelet basis for analyzing the image of the turbulent structures was first discussed. It is found that these orthonormal wavelet families with index N＜10 were inappropriate for multiresolution image analysis of turbulent flow. The multiresolution images of turbulent structures were very similar when using the wavelet basis with the higher index number, even though wavelet bases are different functions. From the image components in orthogonal wavelet spaces with different scales, the further evident of the multi-scale structures in jet can be observed, and the edges of the vortices at different resolutions or scales and the coherent structure can be easily extracted.

Wavelet analysis in two-dimensional tomography

Science.gov (United States)

Burkovets, Dimitry N.

2002-02-01

The diagnostic possibilities of wavelet-analysis of coherent images of connective tissue in its pathological changes diagnostics. The effectiveness of polarization selection in obtaining wavelet-coefficients' images is also shown. The wavelet structures, characterizing the process of skin psoriasis, bone-tissue osteoporosis have been analyzed. The histological sections of physiological normal and pathologically changed samples of connective tissue of human skin and spongy bone tissue have been analyzed.

Bit Plane Coding based Steganography Technique for JPEG2000 Images and Videos

Directory of Open Access Journals (Sweden)

Geeta Kasana

2016-02-01

Full Text Available In this paper, a Bit Plane Coding (BPC based steganography technique for JPEG2000 images and Motion JPEG2000 video is proposed. Embedding in this technique is performed in the lowest significant bit planes of the wavelet coefficients of a cover image. In JPEG2000 standard, the number of bit planes of wavelet coefficients to be used in encoding is dependent on the compression rate and are used in Tier-2 process of JPEG2000. In the proposed technique, Tier-1 and Tier-2 processes of JPEG2000 and Motion JPEG2000 are executed twice on the encoder side to collect the information about the lowest bit planes of all code blocks of a cover image, which is utilized in embedding and transmitted to the decoder. After embedding secret data, Optimal Pixel Adjustment Process (OPAP is applied on stego images to enhance its visual quality. Experimental results show that proposed technique provides large embedding capacity and better visual quality of stego images than existing steganography techniques for JPEG2000 compressed images and videos. Extracted secret image is similar to the original secret image.

A new fractional wavelet transform

Science.gov (United States)

Dai, Hongzhe; Zheng, Zhibao; Wang, Wei

2017-03-01

The fractional Fourier transform (FRFT) is a potent tool to analyze the time-varying signal. However, it fails in locating the fractional Fourier domain (FRFD)-frequency contents which is required in some applications. A novel fractional wavelet transform (FRWT) is proposed to solve this problem. It displays the time and FRFD-frequency information jointly in the time-FRFD-frequency plane. The definition, basic properties, inverse transform and reproducing kernel of the proposed FRWT are considered. It has been shown that an FRWT with proper order corresponds to the classical wavelet transform (WT). The multiresolution analysis (MRA) associated with the developed FRWT, together with the construction of the orthogonal fractional wavelets are also presented. Three applications are discussed: the analysis of signal with time-varying frequency content, the FRFD spectrum estimation of signals that involving noise, and the construction of fractional Harr wavelet. Simulations verify the validity of the proposed FRWT.

Numerical shaping of the ultrasonic wavelet

International Nuclear Information System (INIS)

Bonis, M.

1991-01-01

Improving the performance and the quality of ultrasonic testing requires the numerical control of the shape of the driving signal applied to the piezoelectric transducer. This allows precise shaping of the ultrasonic field wavelet and corrections for the physical defects of the transducer, which are mainly due to the damper or the lens. It also does away with the need for an accurate electric matching. It then becomes feasible to characterize, a priori, the ultrasonic wavelet by means of temporal and/or spectral specifications and to use, subsequently, an adaptative algorithm to calculate the corresponding driving wavelet. Moreover, the versatility resulting from the numerical control of this wavelet allows it to be changed in real time during a test

Wavelet analysis and its applications an introduction

CERN Document Server

Yajnik, Archit

2013-01-01

"Wavelet analysis and its applications: an introduction" demonstrates the consequences of Fourier analysis and introduces the concept of wavelet followed by applications lucidly. While dealing with one dimension signals, sometimes they are required to be oversampled. A novel technique of oversampling the digital signal is introduced in this book alongwith necessary illustrations. The technique of feature extraction in the development of optical character recognition software for any natural language alongwith wavelet based feature extraction technique is demonstrated using multiresolution analysis of wavelet in the book.

Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan, China.

Science.gov (United States)

Zhang, Hong; Zhang, Sheng; Wang, Ping; Qin, Yuzhe; Wang, Huifeng

2017-07-01

Particulate matter with aerodynamic diameter below 10 μm (PM 10 ) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM 10 concentrations. It was evaluated by experiments using a 10-year data set of daily PM 10 concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM 10 concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM 10 concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM 10 concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM 10 concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM 10 forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM 10 time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM 10 time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM 10 time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM 10 forecasting field.

Identification method of gas-liquid two-phase flow regime based on image wavelet packet information entropy and genetic neural network

International Nuclear Information System (INIS)

Zhou Yunlong; Chen Fei; Sun Bin

2008-01-01

Based on the characteristic that wavelet packet transform image can be decomposed by different scales, a flow regime identification method based on image wavelet packet information entropy feature and genetic neural network was proposed. Gas-liquid two-phase flow images were captured by digital high speed video systems in horizontal pipe. The information entropy feature from transformation coefficients were extracted using image processing techniques and multi-resolution analysis. The genetic neural network was trained using those eigenvectors, which was reduced by the principal component analysis, as flow regime samples, and the flow regime intelligent identification was realized. The test result showed that image wavelet packet information entropy feature could excellently reflect the difference between seven typical flow regimes, and the genetic neural network with genetic algorithm and BP algorithm merits were with the characteristics of fast convergence for simulation and avoidance of local minimum. The recognition possibility of the network could reach up to about 100%, and a new and effective method was presented for on-line flow regime. (authors)

A study of non-binary discontinuity wavelet

International Nuclear Information System (INIS)

Lin Hai; Liu Lianshou

2006-01-01

This paper gives a study of non-binary discontinuity wavelet, put forward the theory and method of constituting basic wavelet functions, and has constituted concretely a wavelet function using λ=3.4 as an example. It also conducts a theoretical inference on the decomposition algorithm and reconstruction algorithm of non-binary wavelet, and gives a concrete study of the change of matrix in connection with λ=3.4. In the end, it shows the future of application of the result to the study of high energy collision. (authors)

Wavelet analysis of the nuclear phase space

International Nuclear Information System (INIS)

Jouault, B.; Sebille, F.; De La Mota, V.

1997-01-01

The description of complex systems requires to select and to compact the relevant information. The wavelet theory constitutes an appropriate framework for defining adapted representation bases obtained from a controlled hierarchy of approximations. The optimization of the wavelet analysis depend mainly on the chosen analysis method and wavelet family. Here the analysis of the harmonic oscillator wave function was carried out by considering a Spline bi-orthogonal wavelet base which satisfy the symmetry requirements and can be approximated by simple analytical functions. The goal of this study was to determine a selection criterion allowing to minimize the number of elements considered for an optimal description of the analysed functions. An essential point consists in utilization of the wavelet complementarity and of the scale functions in order to reproduce the oscillating and peripheral parts of the wave functions. The wavelet base representation allows defining a sequence of approximations of the density matrix. Thus, this wavelet representation of the density matrix offers an optimal base for describing both the static nuclear configurations and their time evolution. This information compacting procedure is performed in a controlled manner and preserves the structure of the system wave functions and consequently some of its quantum properties

Wavelets and multiscale signal processing

CERN Document Server

Cohen, Albert

1995-01-01

Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...

Detecting microcalcifications in digital mammogram using wavelets

International Nuclear Information System (INIS)

Yang Jucheng; Park Dongsun

2004-01-01

Breast cancer is still one of main mortality causes in women, but the early detection can increase the chance of cure. Microcalcifications are small size structures, which can indicate the presence of cancer since they are often associated to the most different types of breast tumors. However, they very small size and the X-ray systems limitations lead to constraints to the adequate visualization of such structures, which means that the microcalcifications can be missed many times in mammogram visual examination. In addition, the human eyes are not able to distinguish minimal tonality differences, which can be another constraint when mammogram image presents poor contrast between microcalcifications and the tissues around them. Computer-aided diagnosis (CAD) schemes are being developed in order to increase the probabilities of early detection. To enhance and detect the microcalcifications in the mammograms we use the wavelets transform. From a signal processing point of view, microcalcifications are high frequency components in mammograms. Due to the multi-resolution decomposition capacity of the wavelet transform, we can decompose the image into different resolution levels which sensitive to different frequency bands. By choosing an appropriate wavelet and a right resolution level, we can effectively enhance and detect the microcalcifications in digital mammogram. In this work, we describe a new four-step method for the detection of microcalcifications: segmentation, wavelets transform processing, labeling and post-processing. The segmentation step is to split the breast area into 256x256 segments. For each segmented sub-image, wavelet transform is operated on it. For comparing study wavelet transform method, 4 typical family wavelets and 4 decomposing levels is discussed. We choose four family wavelets for detecting microcalcifications, that is, Daubechies, Biothgonai, Coieflets and Symlets wavelets, for simply, bd4, bior3.7, coif3, sym2 are chosen as the

Applications of a fast, continuous wavelet transform

Energy Technology Data Exchange (ETDEWEB)

Dress, W.B.

1997-02-01

A fast, continuous, wavelet transform, based on Shannon`s sampling theorem in frequency space, has been developed for use with continuous mother wavelets and sampled data sets. The method differs from the usual discrete-wavelet approach and the continuous-wavelet transform in that, here, the wavelet is sampled in the frequency domain. Since Shannon`s sampling theorem lets us view the Fourier transform of the data set as a continuous function in frequency space, the continuous nature of the functions is kept up to the point of sampling the scale-translation lattice, so the scale-translation grid used to represent the wavelet transform is independent of the time- domain sampling of the signal under analysis. Computational cost and nonorthogonality aside, the inherent flexibility and shift invariance of the frequency-space wavelets has advantages. The method has been applied to forensic audio reconstruction speaker recognition/identification, and the detection of micromotions of heavy vehicles associated with ballistocardiac impulses originating from occupants` heart beats. Audio reconstruction is aided by selection of desired regions in the 2-D representation of the magnitude of the transformed signal. The inverse transform is applied to ridges and selected regions to reconstruct areas of interest, unencumbered by noise interference lying outside these regions. To separate micromotions imparted to a mass-spring system (e.g., a vehicle) by an occupants beating heart from gross mechanical motions due to wind and traffic vibrations, a continuous frequency-space wavelet, modeled on the frequency content of a canonical ballistocardiogram, was used to analyze time series taken from geophone measurements of vehicle micromotions. By using a family of mother wavelets, such as a set of Gaussian derivatives of various orders, features such as the glottal closing rate and word and phrase segmentation may be extracted from voice data.

Justification of Estimates for Fiscal Year 1984 Submitted to Congress.

Science.gov (United States)

1983-01-01

completed on reactive opponents and audio ( binaural ) and video display techniques. The major efforts will be in the expansion of the technology to large...teleconferencing will end with the demonstration of the 50 kb color codec for high quality, low bandwidth video. In contrast to the beat existing systems that

Classification of endoscopic capsule images by using color wavelet features, higher order statistics and radial basis functions.

Science.gov (United States)

Lima, C S; Barbosa, D; Ramos, J; Tavares, A; Monteiro, L; Carvalho, L

2008-01-01

This paper presents a system to support medical diagnosis and detection of abnormal lesions by processing capsule endoscopic images. Endoscopic images possess rich information expressed by texture. Texture information can be efficiently extracted from medium scales of the wavelet transform. The set of features proposed in this paper to code textural information is named color wavelet covariance (CWC). CWC coefficients are based on the covariances of second order textural measures, an optimum subset of them is proposed. Third and forth order moments are added to cope with distributions that tend to become non-Gaussian, especially in some pathological cases. The proposed approach is supported by a classifier based on radial basis functions procedure for the characterization of the image regions along the video frames. The whole methodology has been applied on real data containing 6 full endoscopic exams and reached 95% specificity and 93% sensitivity.

A Comparative Study on Optimal Structural Dynamics Using Wavelet Functions

Directory of Open Access Journals (Sweden)

Seyed Hossein Mahdavi

2015-01-01

Full Text Available Wavelet solution techniques have become the focus of interest among researchers in different disciplines of science and technology. In this paper, implementation of two different wavelet basis functions has been comparatively considered for dynamic analysis of structures. For this aim, computational technique is developed by using free scale of simple Haar wavelet, initially. Later, complex and continuous Chebyshev wavelet basis functions are presented to improve the time history analysis of structures. Free-scaled Chebyshev coefficient matrix and operation of integration are derived to directly approximate displacements of the corresponding system. In addition, stability of responses has been investigated for the proposed algorithm of discrete Haar wavelet compared against continuous Chebyshev wavelet. To demonstrate the validity of the wavelet-based algorithms, aforesaid schemes have been extended to the linear and nonlinear structural dynamics. The effectiveness of free-scaled Chebyshev wavelet has been compared with simple Haar wavelet and two common integration methods. It is deduced that either indirect method proposed for discrete Haar wavelet or direct approach for continuous Chebyshev wavelet is unconditionally stable. Finally, it is concluded that numerical solution is highly benefited by the least computation time involved and high accuracy of response, particularly using low scale of complex Chebyshev wavelet.

Wavelet-based verification of the quantitative precipitation forecast

Science.gov (United States)

Yano, Jun-Ichi; Jakubiak, Bogumil

2016-06-01

This paper explores the use of wavelets for spatial verification of quantitative precipitation forecasts (QPF), and especially the capacity of wavelets to provide both localization and scale information. Two 24-h forecast experiments using the two versions of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) on 22 August 2010 over Poland are used to illustrate the method. Strong spatial localizations and associated intermittency of the precipitation field make verification of QPF difficult using standard statistical methods. The wavelet becomes an attractive alternative, because it is specifically designed to extract spatially localized features. The wavelet modes are characterized by the two indices for the scale and the localization. Thus, these indices can simply be employed for characterizing the performance of QPF in scale and localization without any further elaboration or tunable parameters. Furthermore, spatially-localized features can be extracted in wavelet space in a relatively straightforward manner with only a weak dependence on a threshold. Such a feature may be considered an advantage of the wavelet-based method over more conventional "object" oriented verification methods, as the latter tend to represent strong threshold sensitivities. The present paper also points out limits of the so-called "scale separation" methods based on wavelets. Our study demonstrates how these wavelet-based QPF verifications can be performed straightforwardly. Possibilities for further developments of the wavelet-based methods, especially towards a goal of identifying a weak physical process contributing to forecast error, are also pointed out.

Joint Time-Frequency And Wavelet Analysis - An Introduction

Directory of Open Access Journals (Sweden)

Majkowski Andrzej

2014-12-01

Full Text Available A traditional frequency analysis is not appropriate for observation of properties of non-stationary signals. This stems from the fact that the time resolution is not defined in the Fourier spectrum. Thus, there is a need for methods implementing joint time-frequency analysis (t/f algorithms. Practical aspects of some representative methods of time-frequency analysis, including Short Time Fourier Transform, Gabor Transform, Wigner-Ville Transform and Cone-Shaped Transform are described in this paper. Unfortunately, there is no correlation between the width of the time-frequency window and its frequency content in the t/f analysis. This property is not valid in the case of a wavelet transform. A wavelet is a wave-like oscillation, which forms its own “wavelet window”. Compression of the wavelet narrows the window, and vice versa. Individual wavelet functions are well localized in time and simultaneously in scale (the equivalent of frequency. The wavelet analysis owes its effectiveness to the pyramid algorithm described by Mallat, which enables fast decomposition of a signal into wavelet components.

A study of biorthogonal multiple vector-valued wavelets

International Nuclear Information System (INIS)

Han Jincang; Cheng Zhengxing; Chen Qingjiang

2009-01-01

The notion of vector-valued multiresolution analysis is introduced and the concept of biorthogonal multiple vector-valued wavelets which are wavelets for vector fields, is introduced. It is proved that, like in the scalar and multiwavelet case, the existence of a pair of biorthogonal multiple vector-valued scaling functions guarantees the existence of a pair of biorthogonal multiple vector-valued wavelet functions. An algorithm for constructing a class of compactly supported biorthogonal multiple vector-valued wavelets is presented. Their properties are investigated by means of operator theory and algebra theory and time-frequency analysis method. Several biorthogonality formulas regarding these wavelet packets are obtained.

Texture analysis using Gabor wavelets

Science.gov (United States)

Naghdy, Golshah A.; Wang, Jian; Ogunbona, Philip O.

1996-04-01

Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symmetric or odd-symmetric Gabor filters. Computational models employed in the analysis of textures have been motivated by two-dimensional Gabor functions arranged in a multi-channel architecture. More recently wavelets have emerged as a powerful tool for non-stationary signal analysis capable of encoding scale-space information efficiently. A multi-resolution implementation in the form of a dyadic decomposition of the signal of interest has been popularized by many researchers. In this paper, Gabor wavelet configured in a 'rosette' fashion is used as a multi-channel filter-bank feature extractor for texture classification. The 'rosette' spans 360 degrees of orientation and covers frequencies from dc. In the proposed algorithm, the texture images are decomposed by the Gabor wavelet configuration and the feature vectors corresponding to the mean of the outputs of the multi-channel filters extracted. A minimum distance classifier is used in the classification procedure. As a comparison the Gabor filter has been used to classify the same texture images from the Brodatz album and the results indicate the superior discriminatory characteristics of the Gabor wavelet. With the test images used it can be concluded that the Gabor wavelet model is a better approximation of the cortical cell receptive field profiles.

Solution of wave-like equation based on Haar wavelet

Directory of Open Access Journals (Sweden)

Naresh Berwal

2012-11-01

Full Text Available Wavelet transform and wavelet analysis are powerful mathematical tools for many problems. Wavelet also can be applied in numerical analysis. In this paper, we apply Haar wavelet method to solve wave-like equation with initial and boundary conditions known. The fundamental idea of Haar wavelet method is to convert the differential equations into a group of algebraic equations, which involves a finite number or variables. The results and graph show that the proposed way is quite reasonable when compared to exact solution.

Wavelets: Applications to Image Compression-II

Indian Academy of Sciences (India)

Wavelets: Applications to Image Compression-II. Sachin P ... successful application of wavelets in image com- ... b) Soft threshold: In this case, all the coefficients x ..... [8] http://www.jpeg.org} Official site of the Joint Photographic Experts Group.

Effective implementation of wavelet Galerkin method

Science.gov (United States)

Finěk, Václav; Šimunková, Martina

2012-11-01

It was proved by W. Dahmen et al. that an adaptive wavelet scheme is asymptotically optimal for a wide class of elliptic equations. This scheme approximates the solution u by a linear combination of N wavelets and a benchmark for its performance is the best N-term approximation, which is obtained by retaining the N largest wavelet coefficients of the unknown solution. Moreover, the number of arithmetic operations needed to compute the approximate solution is proportional to N. The most time consuming part of this scheme is the approximate matrix-vector multiplication. In this contribution, we will introduce our implementation of wavelet Galerkin method for Poisson equation -Δu = f on hypercube with homogeneous Dirichlet boundary conditions. In our implementation, we identified nonzero elements of stiffness matrix corresponding to the above problem and we perform matrix-vector multiplication only with these nonzero elements.

Application of Improved Wavelet Thresholding Function in Image Denoising Processing

Directory of Open Access Journals (Sweden)

Hong Qi Zhang

2014-07-01

Full Text Available Wavelet analysis is a time – frequency analysis method, time-frequency localization problems are well solved, this paper analyzes the basic principles of the wavelet transform and the relationship between the signal singularity Lipschitz exponent and the local maxima of the wavelet transform coefficients mold, the principles of wavelet transform in image denoising are analyzed, the disadvantages of traditional wavelet thresholding function are studied, wavelet threshold function, the discontinuity of hard threshold and constant deviation of soft threshold are improved, image is denoised through using the improved threshold function.

International Conference and Workshop on Fractals and Wavelets

CERN Document Server

Barnsley, Michael; Devaney, Robert; Falconer, Kenneth; Kannan, V; PB, Vinod

2014-01-01

Fractals and wavelets are emerging areas of mathematics with many common factors which can be used to develop new technologies. This volume contains the selected contributions from the lectures and plenary and invited talks given at the International Workshop and Conference on Fractals and Wavelets held at Rajagiri School of Engineering and Technology, India from November 9-12, 2013. Written by experts, the contributions hope to inspire and motivate researchers working in this area. They provide more insight into the areas of fractals, self similarity, iterated function systems, wavelets and the applications of both fractals and wavelets. This volume will be useful for the beginners as well as experts in the fields of fractals and wavelets.

Signal-dependent independent component analysis by tunable mother wavelets

International Nuclear Information System (INIS)

Seo, Kyung Ho

2006-02-01

The objective of this study is to improve the standard independent component analysis when applied to real-world signals. Independent component analysis starts from the assumption that signals from different physical sources are statistically independent. But real-world signals such as EEG, ECG, MEG, and fMRI signals are not statistically independent perfectly. By definition, standard independent component analysis algorithms are not able to estimate statistically dependent sources, that is, when the assumption of independence does not hold. Therefore before independent component analysis, some preprocessing stage is needed. This paper started from simple intuition that wavelet transformed source signals by 'well-tuned' mother wavelet will be simplified sufficiently, and then the source separation will show better results. By the correlation coefficient method, the tuning process between source signal and tunable mother wavelet was executed. Gamma component of raw EEG signal was set to target signal, and wavelet transform was executed by tuned mother wavelet and standard mother wavelets. Simulation results by these wavelets was shown

Quantum dynamics and electronic spectroscopy within the framework of wavelets

International Nuclear Information System (INIS)

Toutounji, Mohamad

2013-01-01

This paper serves as a first-time report on formulating important aspects of electronic spectroscopy and quantum dynamics in condensed harmonic systems using the framework of wavelets, and a stepping stone to our future work on developing anharmonic wavelets. The Morlet wavelet is taken to be the mother wavelet for the initial state of the system of interest. This work reports daughter wavelets that may be used to study spectroscopy and dynamics of harmonic systems. These wavelets are shown to arise naturally upon optical electronic transition of the system of interest. Natural birth of basis (daughter) wavelets emerging on exciting an electronic two-level system coupled, both linearly and quadratically, to harmonic phonons is discussed. It is shown that this takes place through using the unitary dilation and translation operators, which happen to be part of the time evolution operator of the final electronic state. The corresponding optical autocorrelation function and linear absorption spectra are calculated to test the applicability and correctness of the herein results. The link between basis wavelets and the Liouville space generating function is established. An anharmonic mother wavelet is also proposed in the case of anharmonic electron–phonon coupling. A brief description of deriving anharmonic wavelets and the corresponding anharmonic Liouville space generating function is explored. In conclusion, a mother wavelet (be it harmonic or anharmonic) which accounts for Duschinsky mixing is suggested. (paper)

Early detection of rogue waves by the wavelet transforms

International Nuclear Information System (INIS)

Bayındır, Cihan

2016-01-01

Highlights: • The advantages of wavelet analysis over the Fourier analysis for the early detection of rogue waves are discussed. • The triangular wavelet spectra can be detected at early stages of the development of rogue waves. • The wavelet analysis is capable of detecting not only the emergence but also the location of a rogue wave. • Wavelet analysis is also capable of predicting the characteristic distances between successive rogue waves. - Abstract: We discuss the possible advantages of using the wavelet transform over the Fourier transform for the early detection of rogue waves. We show that the triangular wavelet spectra of the rogue waves can be detected at early stages of the development of rogue waves in a chaotic wave field. Compared to the Fourier spectra, the wavelet spectra are capable of detecting not only the emergence of a rogue wave but also its possible spatial (or temporal) location. Due to this fact, wavelet transform is also capable of predicting the characteristic distances between successive rogue waves. Therefore multiple simultaneous breaking of the successive rogue waves on ships or on the offshore structures can be predicted and avoided by smart designs and operations.

Early detection of rogue waves by the wavelet transforms

Energy Technology Data Exchange (ETDEWEB)

Bayındır, Cihan, E-mail: cihan.bayindir@isikun.edu.tr

2016-01-08

Highlights: • The advantages of wavelet analysis over the Fourier analysis for the early detection of rogue waves are discussed. • The triangular wavelet spectra can be detected at early stages of the development of rogue waves. • The wavelet analysis is capable of detecting not only the emergence but also the location of a rogue wave. • Wavelet analysis is also capable of predicting the characteristic distances between successive rogue waves. - Abstract: We discuss the possible advantages of using the wavelet transform over the Fourier transform for the early detection of rogue waves. We show that the triangular wavelet spectra of the rogue waves can be detected at early stages of the development of rogue waves in a chaotic wave field. Compared to the Fourier spectra, the wavelet spectra are capable of detecting not only the emergence of a rogue wave but also its possible spatial (or temporal) location. Due to this fact, wavelet transform is also capable of predicting the characteristic distances between successive rogue waves. Therefore multiple simultaneous breaking of the successive rogue waves on ships or on the offshore structures can be predicted and avoided by smart designs and operations.

Using wavelet features for analyzing gamma lines

International Nuclear Information System (INIS)

Medhat, M.E.; Abdel-hafiez, A.; Hassan, M.F.; Ali, M.A.; Uzhinskii, V.V.

2004-01-01

Data processing methods for analyzing gamma ray spectra with symmetric bell-shaped peaks form are considered. In many cases the peak form is symmetrical bell shaped in particular a Gaussian case is the most often used due to many physical reasons. The problem is how to evaluate parameters of such peaks, i.e. their positions, amplitudes and also their half-widths, that is for a single peak and overlapped peaks. Through wavelet features by using Marr wavelet (Mexican Hat) as a correlation method, it could be to estimate the optimal wavelet parameters and to locate peaks in the spectrum. The performance of the proposed method and others shows a better quality of wavelet transform method

Wavelets and quantum algebras

International Nuclear Information System (INIS)

Ludu, A.; Greiner, M.

1995-09-01

A non-linear associative algebra is realized in terms of translation and dilation operators, and a wavelet structure generating algebra is obtained. We show that this algebra is a q-deformation of the Fourier series generating algebra, and reduces to this for certain value of the deformation parameter. This algebra is also homeomorphic with the q-deformed su q (2) algebra and some of its extensions. Through this algebraic approach new methods for obtaining the wavelets are introduced. (author). 20 refs

Noise reduction by wavelet thresholding

National Research Council Canada - National Science Library

Jansen, Maarten

2001-01-01

.... I rather present new material and own insights in the que stions involved with wavelet based noise reduction . On the other hand , the presented material does cover a whole range of methodologies, and in that sense, the book may serve as an introduction into the domain of wavelet smoothing. Throughout the text, three main properties show up ever again: spar...

Wavelets for the stimulation of turbulent incompressible flows

International Nuclear Information System (INIS)

Deriaz, E.

2006-02-01

This PhD thesis presents original wavelet methods aimed at simulating incompressible fluids. In order to construct 2D and 3D wavelets designed for incompressible flows, we resume P-G Lemarie-Rieussets and K. Urbans works on divergence free wavelets. We show the existence of associated fast algorithms. In the following, we use divergence-free wavelet construction to define the Helmholtz decomposition of 2D and 3D vector fields. All these algorithms provide a new method for the numerical resolution of the incompressible Navier-Stokes equations. (author)

Implementation of Texture Based Image Retrieval Using M-band Wavelet Transform

Institute of Scientific and Technical Information of China (English)

LiaoYa-li; Yangyan; CaoYang

2003-01-01

Wavelet transform has attracted attention because it is a very useful tool for signal analyzing. As a fundamental characteristic of an image, texture traits play an important role in the human vision system for recognition and interpretation of images. The paper presents an approach to implement texture-based image retrieval using M-band wavelet transform. Firstly the traditional 2-band wavelet is extended to M-band wavelet transform. Then the wavelet moments are computed by M-band wavelet coefficients in the wavelet domain. The set of wavelet moments forms the feature vector related to the texture distribution of each wavelet images. The distances between the feature vectors describe the similarities of different images. The experimental result shows that the M-band wavelet moment features of the images are effective for image indexing.The retrieval method has lower computational complexity, yet it is capable of giving better retrieval performance for a given medical image database.

Selection of the wavelet function for the frequencies estimation; Seleccion de la funcion wavelet para la estimacion de frecuencias

Energy Technology Data Exchange (ETDEWEB)

Garcia R, A. [ININ, Carretera Mexico-Toluca S/N, 52750 La Marquesa, Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: ramador@nuclear.inin.mx

2007-07-01

At the moment the signals are used to diagnose the state of the systems, by means of the extraction of their more important characteristics such as the frequencies, tendencies, changes and temporary evolutions. This characteristics are detected by means of diverse analysis techniques, as Autoregressive methods, Fourier Transformation, Fourier transformation in short time, Wavelet transformation, among others. The present work uses the one Wavelet transformation because it allows to analyze stationary, quasi-stationary and transitory signals in the time-frequency plane. It also describes a methodology to select the scales and the Wavelet function to be applied the one Wavelet transformation with the objective of detecting to the dominant system frequencies. (Author)

Image and video compression for multimedia engineering fundamentals, algorithms, and standards

CERN Document Server

Shi, Yun Q

2008-01-01

Part I: Fundamentals Introduction Quantization Differential Coding Transform Coding Variable-Length Coding: Information Theory Results (II) Run-Length and Dictionary Coding: Information Theory Results (III) Part II: Still Image Compression Still Image Coding: Standard JPEG Wavelet Transform for Image Coding: JPEG2000 Nonstandard Still Image Coding Part III: Motion Estimation and Compensation Motion Analysis and Motion Compensation Block Matching Pel-Recursive Technique Optical Flow Further Discussion and Summary on 2-D Motion Estimation Part IV: Video Compression Fundam

Optimization of wavelet decomposition for image compression and feature preservation.

Science.gov (United States)

Lo, Shih-Chung B; Li, Huai; Freedman, Matthew T

2003-09-01

A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images. We found that the Daubechies wavelet or those wavelets with similar filtering characteristics can produce the highest compression efficiency with the smallest mean-square-error for many image patterns including general image textures as well as microcalcifications in digital mammograms. However, the Haar wavelet produces the best results on sharp edges and low-noise smooth areas. We also found that a special wavelet whose low-pass filter coefficients are 0.32252136, 0.85258927, 1.38458542, and -0.14548269) produces the best preservation outcomes in all tested microcalcification features including the peak signal-to-noise ratio, the contrast and the figure of merit in the wavelet lossy compression scheme. Having analyzed the spectrum of the wavelet filters, we can find the compression outcomes and feature preservation characteristics as a function of wavelets. This newly developed optimization approach can be generalized to other image analysis applications where a wavelet decomposition is employed.

Nuclear data compression and reconstruction via discrete wavelet transform

Energy Technology Data Exchange (ETDEWEB)

Park, Young Ryong; Cho, Nam Zin [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1998-12-31

Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that the signal compression using wavelet is very effective to reduce the data saving spaces. 7 refs., 4 figs., 3 tabs. (Author)

Nuclear data compression and reconstruction via discrete wavelet transform

Energy Technology Data Exchange (ETDEWEB)

Park, Young Ryong; Cho, Nam Zin [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1997-12-31

Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that the signal compression using wavelet is very effective to reduce the data saving spaces. 7 refs., 4 figs., 3 tabs. (Author)

Construction of a class of Daubechies type wavelet bases

International Nuclear Information System (INIS)

Li Dengfeng; Wu Guochang

2009-01-01

Extensive work has been done in the theory and the construction of compactly supported orthonormal wavelet bases of L 2 (R). Some of the most distinguished work was done by Daubechies, who constructed a whole family of such wavelet bases. In this paper, we construct a class of orthonormal wavelet bases by using the principle of Daubechies, and investigate the length of support and the regularity of these wavelet bases.

Online Wavelet Complementary velocity Estimator.

Science.gov (United States)

Righettini, Paolo; Strada, Roberto; KhademOlama, Ehsan; Valilou, Shirin

2018-02-01

In this paper, we have proposed a new online Wavelet Complementary velocity Estimator (WCE) over position and acceleration data gathered from an electro hydraulic servo shaking table. This is a batch estimator type that is based on the wavelet filter banks which extract the high and low resolution of data. The proposed complementary estimator combines these two resolutions of velocities which acquired from numerical differentiation and integration of the position and acceleration sensors by considering a fixed moving horizon window as input to wavelet filter. Because of using wavelet filters, it can be implemented in a parallel procedure. By this method the numerical velocity is estimated without having high noise of differentiators, integration drifting bias and with less delay which is suitable for active vibration control in high precision Mechatronics systems by Direct Velocity Feedback (DVF) methods. This method allows us to make velocity sensors with less mechanically moving parts which makes it suitable for fast miniature structures. We have compared this method with Kalman and Butterworth filters over stability, delay and benchmarked them by their long time velocity integration for getting back the initial position data. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Visibility of wavelet quantization noise

Science.gov (United States)

Watson, A. B.; Yang, G. Y.; Solomon, J. A.; Villasenor, J.

1997-01-01

The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

Application of wavelets in speech processing

CERN Document Server

Farouk, Mohamed Hesham

2014-01-01

This book provides a survey on wide-spread of employing wavelets analysis  in different applications of speech processing. The author examines development and research in different application of speech processing. The book also summarizes the state of the art research on wavelet in speech processing.

From cardinal spline wavelet bases to highly coherent dictionaries

International Nuclear Information System (INIS)

Andrle, Miroslav; Rebollo-Neira, Laura

2008-01-01

Wavelet families arise by scaling and translations of a prototype function, called the mother wavelet. The construction of wavelet bases for cardinal spline spaces is generally carried out within the multi-resolution analysis scheme. Thus, the usual way of increasing the dimension of the multi-resolution subspaces is by augmenting the scaling factor. We show here that, when working on a compact interval, the identical effect can be achieved without changing the wavelet scale but reducing the translation parameter. By such a procedure we generate a redundant frame, called a dictionary, spanning the same spaces as a wavelet basis but with wavelets of broader support. We characterize the correlation of the dictionary elements by measuring their 'coherence' and produce examples illustrating the relevance of highly coherent dictionaries to problems of sparse signal representation. (fast track communication)

Wavelet series approximation using wavelet function with compactly ...

African Journals Online (AJOL)

The Wavelets generated by Scaling Function with Compactly Support are useful in various applications especially for reconstruction of functions. Generally, the computational process will be faster if Scaling Function support descends, so computational errors are summarized from one level to another level. In this article, the ...

Perceptual coding of stereo endoscopy video for minimally invasive surgery

Science.gov (United States)

Bartoli, Guido; Menegaz, Gloria; Yang, Guang Zhong

2007-03-01

In this paper, we propose a compression scheme that is tailored for stereo-laparoscope sequences. The inter-frame correlation is modeled by the deformation field obtained by elastic registration between two subsequent frames and exploited for prediction of the left sequence. The right sequence is lossy encoded by prediction from the corresponding left images. Wavelet-based coding is applied to both the deformation vector fields and residual images. The resulting system supports spatio temporal scalability, while providing lossless performance. The implementation of the wavelet transform by integer lifting ensures a low computational complexity, thus reducing the required run-time memory allocation and on line implementation. Extensive psychovisual tests were performed for system validation and characterization with respect to the MPEG4 standard for video coding. Results are very encouraging: the PSVC system features the functionalities making it suitable for PACS while providing a good trade-off between usability and performance in lossy mode.

Wavelet tree structure based speckle noise removal for optical coherence tomography

Science.gov (United States)

Yuan, Xin; Liu, Xuan; Liu, Yang

2018-02-01

We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.

Wavelet processing techniques for digital mammography

Science.gov (United States)

Laine, Andrew F.; Song, Shuwu

1992-09-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Similar to traditional coarse to fine matching strategies, the radiologist may first choose to look for coarse features (e.g., dominant mass) within low frequency levels of a wavelet transform and later examine finer features (e.g., microcalcifications) at higher frequency levels. In addition, features may be extracted by applying geometric constraints within each level of the transform. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet representations, enhanced by linear, exponential and constant weight functions through scale space. By improving the visualization of breast pathology we can improve the chances of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

Application of wavelet transform in seismic signal processing

International Nuclear Information System (INIS)

Ghasemi, M. R.; Mohammadzadeh, A.; Salajeghe, E.

2005-01-01

Wavelet transform is a new tool for signal analysis which can perform a simultaneous signal time and frequency representations. Under Multi Resolution Analysis, one can quickly determine details for signals and their properties using Fast Wavelet Transform algorithms. In this paper, for a better physical understanding of a signal and its basic algorithms, Multi Resolution Analysis together with wavelet transforms in a form of Digital Signal Processing will be discussed. For a Seismic Signal Processing, sets of Orthonormal Daubechies Wavelets are suggested. when dealing with the application of wavelets in SSP, one may discuss about denoising from the signal and data compression existed in the signal, which is important in seismic signal data processing. Using this techniques, EL-Centro and Nagan signals were remodeled with a 25% of total points, resulted in a satisfactory results with an acceptable error drift. Thus a total of 1559 and 2500 points for EL-centro and Nagan seismic curves each, were reduced to 389 and 625 points respectively, with a very reasonable error drift, details of which are recorded in the paper. Finally, the future progress in signal processing, based on wavelet theory will be appointed

Denoising in Wavelet Packet Domain via Approximation Coefficients

Directory of Open Access Journals (Sweden)

Zahra Vahabi

2012-01-01

Full Text Available In this paper we propose a new approach in the wavelet domain for image denoising. In recent researches wavelet transform has introduced a time-Frequency transform for computing wavelet coefficient and eliminating noise. Some coefficients have effected smaller than the other's from noise, so they can be use reconstruct images with other subbands. We have developed Approximation image to estimate better denoised image. Naturally noiseless subimage introduced image with lower noise. Beside denoising we obtain a bigger compression rate. Increasing image contrast is another advantage of this method. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.100 images of LIVE Dataset were tested, comparing signal to noise ratios (SNR,soft thresholding was %1.12 better than hard thresholding, POAC was %1.94 better than soft thresholding and POAC with wavelet packet was %1.48 better than POAC.

Pseudo-stochastic signal characterization in wavelet-domain

International Nuclear Information System (INIS)

Zaytsev, Kirill I; Zhirnov, Andrei A; Alekhnovich, Valentin I; Yurchenko, Stanislav O

2015-01-01

In this paper we present the method for fast and accurate characterization of pseudo-stochastic signals, which contain a large number of similar but randomly-located fragments. This method allows estimating the statistical characteristics of pseudo-stochastic signal, and it is based on digital signal processing in wavelet-domain. Continuous wavelet transform and the criterion for wavelet scale power density are utilized. We are experimentally implementing this method for the purpose of sand granulometry, and we are estimating the statistical parameters of test sand fractions

WAVELET TRANSFORM AND LIP MODEL

Directory of Open Access Journals (Sweden)

Guy Courbebaisse

2011-05-01

Full Text Available The Fourier transform is well suited to the study of stationary functions. Yet, it is superseded by the Wavelet transform for the powerful characterizations of function features such as singularities. On the other hand, the LIP (Logarithmic Image Processing model is a mathematical framework developed by Jourlin and Pinoli, dedicated to the representation and processing of gray tones images called hereafter logarithmic images. This mathematically well defined model, comprising a Fourier Transform "of its own", provides an effective tool for the representation of images obtained by transmitted light, such as microscope images. This paper presents a Wavelet transform within the LIP framework, with preservation of the classical Wavelet Transform properties. We show that the fast computation algorithm due to Mallat can be easily used. An application is given for the detection of crests.

From Calculus to Wavelets: ANew Mathematical Technique

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 4. From Calculus to Wavelets: A New Mathematical Technique Wavelet Analysis Physical Properties. Gerald B Folland. General Article Volume 2 Issue 4 April 1997 pp 25-37 ...

On transforms between Gabor frames and wavelet frames

DEFF Research Database (Denmark)

Christensen, Ole; Goh, Say Song

2013-01-01

We describe a procedure that enables us to construct dual pairs of wavelet frames from certain dual pairs of Gabor frames. Applying the construction to Gabor frames generated by appropriate exponential Bsplines gives wavelet frames generated by functions whose Fourier transforms are compactly...... supported splines with geometrically distributed knot sequences. There is also a reverse transform, which yields pairs of dual Gabor frames when applied to certain wavelet frames....

Application of wavelets to singular integral scattering equations

International Nuclear Information System (INIS)

Kessler, B.M.; Payne, G.L.; Polyzou, W.N.

2004-01-01

The use of orthonormal wavelet basis functions for solving singular integral scattering equations is investigated. It is shown that these basis functions lead to sparse matrix equations which can be solved by iterative techniques. The scaling properties of wavelets are used to derive an efficient method for evaluating the singular integrals. The accuracy and efficiency of the wavelet transforms are demonstrated by solving the two-body T-matrix equation without partial wave projection. The resulting matrix equation which is characteristic of multiparticle integral scattering equations is found to provide an efficient method for obtaining accurate approximate solutions to the integral equation. These results indicate that wavelet transforms may provide a useful tool for studying few-body systems

Coresident sensor fusion and compression using the wavelet transform

Energy Technology Data Exchange (ETDEWEB)

Yocky, D.A.

1996-03-11

Imagery from coresident sensor platforms, such as unmanned aerial vehicles, can be combined using, multiresolution decomposition of the sensor images by means of the two-dimensional wavelet transform. The wavelet approach uses the combination of spatial/spectral information at multiple scales to create a fused image. This can be done in both an ad hoc or model-based approach. We compare results from commercial ``fusion`` software and the ad hoc, wavelet approach. Results show the wavelet approach outperforms the commercial algorithms and also supports efficient compression of the fused image.

Framelets and wavelets algorithms, analysis, and applications

CERN Document Server

Han, Bin

2017-01-01

Marking a distinct departure from the perspectives of frame theory and discrete transforms, this book provides a comprehensive mathematical and algorithmic introduction to wavelet theory. As such, it can be used as either a textbook or reference guide. As a textbook for graduate mathematics students and beginning researchers, it offers detailed information on the basic theory of framelets and wavelets, complemented by self-contained elementary proofs, illustrative examples/figures, and supplementary exercises. Further, as an advanced reference guide for experienced researchers and practitioners in mathematics, physics, and engineering, the book addresses in detail a wide range of basic and advanced topics (such as multiwavelets/multiframelets in Sobolev spaces and directional framelets) in wavelet theory, together with systematic mathematical analysis, concrete algorithms, and recent developments in and applications of framelets and wavelets. Lastly, the book can also be used to teach on or study selected spe...

Scalets, wavelets and (complex) turning point quantization

Science.gov (United States)

Handy, C. R.; Brooks, H. A.

2001-05-01

Despite the many successes of wavelet analysis in image and signal processing, the incorporation of continuous wavelet transform theory within quantum mechanics has lacked a compelling, first principles, motivating analytical framework, until now. For arbitrary one-dimensional rational fraction Hamiltonians, we develop a simple, unified formalism, which clearly underscores the complementary, and mutually interdependent, role played by moment quantization theory (i.e. via scalets, as defined herein) and wavelets. This analysis involves no approximation of the Hamiltonian within the (equivalent) wavelet space, and emphasizes the importance of (complex) multiple turning point contributions in the quantization process. We apply the method to three illustrative examples. These include the (double-well) quartic anharmonic oscillator potential problem, V(x) = Z2x2 + gx4, the quartic potential, V(x) = x4, and the very interesting and significant non-Hermitian potential V(x) = -(ix)3, recently studied by Bender and Boettcher.

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

Science.gov (United States)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at

Time-frequency analysis of phonocardiogram signals using wavelet transform: a comparative study.

Science.gov (United States)

Ergen, Burhan; Tatar, Yetkin; Gulcur, Halil Ozcan

2012-01-01

Analysis of phonocardiogram (PCG) signals provides a non-invasive means to determine the abnormalities caused by cardiovascular system pathology. In general, time-frequency representation (TFR) methods are used to study the PCG signal because it is one of the non-stationary bio-signals. The continuous wavelet transform (CWT) is especially suitable for the analysis of non-stationary signals and to obtain the TFR, due to its high resolution, both in time and in frequency and has recently become a favourite tool. It decomposes a signal in terms of elementary contributions called wavelets, which are shifted and dilated copies of a fixed mother wavelet function, and yields a joint TFR. Although the basic characteristics of the wavelets are similar, each type of the wavelets produces a different TFR. In this study, eight real types of the most known wavelets are examined on typical PCG signals indicating heart abnormalities in order to determine the best wavelet to obtain a reliable TFR. For this purpose, the wavelet energy and frequency spectrum estimations based on the CWT and the spectra of the chosen wavelets were compared with the energy distribution and the autoregressive frequency spectra in order to determine the most suitable wavelet. The results show that Morlet wavelet is the most reliable wavelet for the time-frequency analysis of PCG signals.

A New Formula for the Inverse Wavelet Transform

OpenAIRE

Sun, Wenchang

2010-01-01

Finding a computationally efficient algorithm for the inverse continuous wavelet transform is a fundamental topic in applications. In this paper, we show the convergence of the inverse wavelet transform.

Adapted wavelet analysis from theory to software

CERN Document Server

Wickerhauser, Mladen Victor

1994-01-01

This detail-oriented text is intended for engineers and applied mathematicians who must write computer programs to perform wavelet and related analysis on real data. It contains an overview of mathematical prerequisites and proceeds to describe hands-on programming techniques to implement special programs for signal analysis and other applications. From the table of contents: - Mathematical Preliminaries - Programming Techniques - The Discrete Fourier Transform - Local Trigonometric Transforms - Quadrature Filters - The Discrete Wavelet Transform - Wavelet Packets - The Best Basis Algorithm - Multidimensional Library Trees - Time-Frequency Analysis - Some Applications - Solutions to Some of the Exercises - List of Symbols - Quadrature Filter Coefficients

Time-localized wavelet multiple regression and correlation

Science.gov (United States)

Fernández-Macho, Javier

2018-02-01

This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multiscale analysis of the comovements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial 'contagion'.

Low-complexity wavelet-based image/video coding for home-use and remote surveillance

NARCIS (Netherlands)

Loomans, M.J.H.; Koeleman, C.J.; Joosen, K.M.J.; With, de P.H.N.

2011-01-01

The availability of inexpensive cameras enables alternative applications beyond personal video communication. For example, surveillance of rooms and home premises is such an alternative application, which can be extended with remote viewing on hand-held battery-powered consumer devices. Scalable

Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

Energy Technology Data Exchange (ETDEWEB)

Anant, K.S.

1997-06-01

In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the P as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the

Wavelets in medical imaging

International Nuclear Information System (INIS)

Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H.

2012-01-01

The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

Wavelets in medical imaging

Energy Technology Data Exchange (ETDEWEB)

Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H. [Sharda University, SET, Department of Electronics and Communication, Knowledge Park 3rd, Gr. Noida (India); University of Kocaeli, Department of Mathematics, 41380 Kocaeli (Turkey); Istanbul Aydin University, Department of Computer Engineering, 34295 Istanbul (Turkey); Sharda University, SET, Department of Mathematics, 32-34 Knowledge Park 3rd, Greater Noida (India)

2012-07-17

The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

Digital transceiver implementation for wavelet packet modulation

Science.gov (United States)

Lindsey, Alan R.; Dill, Jeffrey C.

1998-03-01

Current transceiver designs for wavelet-based communication systems are typically reliant on analog waveform synthesis, however, digital processing is an important part of the eventual success of these techniques. In this paper, a transceiver implementation is introduced for the recently introduced wavelet packet modulation scheme which moves the analog processing as far as possible toward the antenna. The transceiver is based on the discrete wavelet packet transform which incorporates level and node parameters for generalized computation of wavelet packets. In this transform no particular structure is imposed on the filter bank save dyadic branching, and a maximum level which is specified a priori and dependent mainly on speed and/or cost considerations. The transmitter/receiver structure takes a binary sequence as input and, based on the desired time- frequency partitioning, processes the signal through demultiplexing, synthesis, analysis, multiplexing and data determination completely in the digital domain - with exception of conversion in and out of the analog domain for transmission.

Multiscale wavelet representations for mammographic feature analysis

Science.gov (United States)

Laine, Andrew F.; Song, Shuwu

1992-12-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

Multi-Level Wavelet Shannon Entropy-Based Method for Single-Sensor Fault Location

Directory of Open Access Journals (Sweden)

Qiaoning Yang

2015-10-01

Full Text Available In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection. In this paper, two new multi-level wavelet Shannon entropies (multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are defined. They take full advantage of sensor fault frequency distribution and energy distribution across multi-subband in wavelet domain. Based on the multi-level wavelet Shannon entropy, a method is proposed for single sensor fault location. The method firstly uses a criterion of maximum energy-to-Shannon entropy ratio to select the appropriate wavelet base for signal analysis. Then multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are used to locate the fault. The method is validated using practical chemical gas concentration data from a gas sensor array. Compared with wavelet time Shannon entropy and wavelet energy Shannon entropy, the experimental results demonstrate that the proposed method can achieve accurate location of a single sensor fault and has good anti-noise ability. The proposed method is feasible and effective for single-sensor fault location.

Electromagnetic spatial coherence wavelets

International Nuclear Information System (INIS)

Castaneda, R.; Garcia-Sucerquia, J.

2005-10-01

The recently introduced concept of spatial coherence wavelets is generalized for describing the propagation of electromagnetic fields in the free space. For this aim, the spatial coherence wavelet tensor is introduced as an elementary amount, in terms of which the formerly known quantities for this domain can be expressed. It allows analyzing the relationship between the spatial coherence properties and the polarization state of the electromagnetic wave. This approach is completely consistent with the recently introduced unified theory of coherence and polarization for random electromagnetic beams, but it provides a further insight about the causal relationship between the polarization states at different planes along the propagation path. (author)

Fast generation of computer-generated holograms using wavelet shrinkage.

Science.gov (United States)

Shimobaba, Tomoyoshi; Ito, Tomoyoshi

2017-01-09

Computer-generated holograms (CGHs) are generated by superimposing complex amplitudes emitted from a number of object points. However, this superposition process remains very time-consuming even when using the latest computers. We propose a fast calculation algorithm for CGHs that uses a wavelet shrinkage method, eliminating small wavelet coefficient values to express approximated complex amplitudes using only a few representative wavelet coefficients.

Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

Science.gov (United States)

Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

2015-01-01

Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

Noise removal for medical X-ray images in wavelet domain

International Nuclear Information System (INIS)

Wang, Ling; Lu, Jianming; Li, Yeqiu; Yahagi, Takashi; Okamoto, Takahide

2006-01-01

Many important problems in engineering and science are well-modeled by Poisson noise, the noise of medical X-ray image is Poisson noise. In this paper, we propose a method of noise removal for degraded medical X-ray image using improved preprocessing and improved BayesShrink (IBS) method in wavelet domain. Firstly, we pre-process the medical X-ray image, Secondly, we apply the Daubechies (db) wavelet transform to medical X-ray image to acquire scaling and wavelet coefficients. Thirdly, we apply the proposed IBS method to process wavelet coefficients. Finally, we compute the inverse wavelet transform for the thresholded coefficeints. Experimental results show that the proposed method always outperforms traditional methods. (author)

Spatial resolution enhancement residual coding using hybrid ...

Indian Academy of Sciences (India)

ble value of the parameters (ρ1,ρ2,θ) in their respective ranges. For each block ... Dirac was developed by BBC and aimed at a royalty-free, open technology (Dirac video codec [online]. ..... In: Acoustics, Speech, and Signal Processing, 1995.

An introduction to random vibrations, spectral & wavelet analysis

CERN Document Server

Newland, D E

2005-01-01

One of the first engineering books to cover wavelet analysis, this classic text describes and illustrates basic theory, with a detailed explanation of the workings of discrete wavelet transforms. Computer algorithms are explained and supported by examples and a set of problems, and an appendix lists ten computer programs for calculating and displaying wavelet transforms.Starting with an introduction to probability distributions and averages, the text examines joint probability distributions, ensemble averages, and correlation; Fourier analysis; spectral density and excitation response relation

Directional dual-tree rational-dilation complex wavelet transform.

Science.gov (United States)

Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin

2014-01-01

Dyadic discrete wavelet transform (DWT) has been used successfully in processing signals having non-oscillatory transient behaviour. However, due to the low Q-factor property of their wavelet atoms, the dyadic DWT is less effective in processing oscillatory signals such as embolic signals (ESs). ESs are extracted from quadrature Doppler signals, which are the output of Doppler ultrasound systems. In order to process ESs, firstly, a pre-processing operation known as phase filtering for obtaining directional signals from quadrature Doppler signals must be employed. Only then, wavelet based methods can be applied to these directional signals for further analysis. In this study, a directional dual-tree rational-dilation complex wavelet transform, which can be applied directly to quadrature signals and has the ability of extracting directional information during analysis, is introduced.

An Extension of Fourier-Wavelet Volume Rendering by View Interpolation

NARCIS (Netherlands)

Westenberg, Michel A.; Roerdink, Jos B.T.M.

2001-01-01

This paper describes an extension to Fourier-wavelet volume rendering (FWVR), which is a Fourier domain implementation of the wavelet X-ray transform. This transform combines integration along the line of sight with a simultaneous 2-D wavelet transform in the view plane perpendicular to this line.

Abnormal traffic flow data detection based on wavelet analysis

Directory of Open Access Journals (Sweden)

Xiao Qian

2016-01-01

Full Text Available In view of the traffic flow data of non-stationary, the abnormal data detection is difficult.proposed basing on the wavelet analysis and least squares method of abnormal traffic flow data detection in this paper.First using wavelet analysis to make the traffic flow data of high frequency and low frequency component and separation, and then, combined with least square method to find abnormal points in the reconstructed signal data.Wavelet analysis and least square method, the simulation results show that using wavelet analysis of abnormal traffic flow data detection, effectively reduce the detection results of misjudgment rate and false negative rate.

Option pricing from wavelet-filtered financial series

Science.gov (United States)

de Almeida, V. T. X.; Moriconi, L.

2012-10-01

We perform wavelet decomposition of high frequency financial time series into large and small time scale components. Taking the FTSE100 index as a case study, and working with the Haar basis, it turns out that the small scale component defined by most (≃99.6%) of the wavelet coefficients can be neglected for the purpose of option premium evaluation. The relevance of the hugely compressed information provided by low-pass wavelet-filtering is related to the fact that the non-gaussian statistical structure of the original financial time series is essentially preserved for expiration times which are larger than just one trading day.

Wavelet-domain de-noising of OCT images of human brain malignant glioma

Science.gov (United States)

Dolganova, I. N.; Aleksandrova, P. V.; Beshplav, S.-I. T.; Chernomyrdin, N. V.; Dubyanskaya, E. N.; Goryaynov, S. A.; Kurlov, V. N.; Reshetov, I. V.; Potapov, A. A.; Tuchin, V. V.; Zaytsev, K. I.

2018-04-01

We have proposed a wavelet-domain de-noising technique for imaging of human brain malignant glioma by optical coherence tomography (OCT). It implies OCT image decomposition using the direct fast wavelet transform, thresholding of the obtained wavelet spectrum and further inverse fast wavelet transform for image reconstruction. By selecting both wavelet basis and thresholding procedure, we have found an optimal wavelet filter, which application improves differentiation of the considered brain tissue classes - i.e. malignant glioma and normal/intact tissue. Namely, it allows reducing the scattering noise in the OCT images and retaining signal decrement for each tissue class. Therefore, the observed results reveals the wavelet-domain de-noising as a prospective tool for improved characterization of biological tissue using the OCT.

Analysis on Behaviour of Wavelet Coefficient during Fault Occurrence in Transformer

Science.gov (United States)

Sreewirote, Bancha; Ngaopitakkul, Atthapol

2018-03-01

The protection system for transformer has play significant role in avoiding severe damage to equipment when disturbance occur and ensure overall system reliability. One of the methodology that widely used in protection scheme and algorithm is discrete wavelet transform. However, characteristic of coefficient under fault condition must be analyzed to ensure its effectiveness. So, this paper proposed study and analysis on wavelet coefficient characteristic when fault occur in transformer in both high- and low-frequency component from discrete wavelet transform. The effect of internal and external fault on wavelet coefficient of both fault and normal phase has been taken into consideration. The fault signal has been simulate using transmission connected to transformer experimental setup on laboratory level that modelled after actual system. The result in term of wavelet coefficient shown a clearly differentiate between wavelet characteristic in both high and low frequency component that can be used to further design and improve detection and classification algorithm that based on discrete wavelet transform methodology in the future.

Joint Markov Blankets in Feature Sets Extracted from Wavelet Packet Decompositions

Directory of Open Access Journals (Sweden)

Gert Van Dijck

2011-07-01

Full Text Available Since two decades, wavelet packet decompositions have been shown effective as a generic approach to feature extraction from time series and images for the prediction of a target variable. Redundancies exist between the wavelet coefficients and between the energy features that are derived from the wavelet coefficients. We assess these redundancies in wavelet packet decompositions by means of the Markov blanket filtering theory. We introduce the concept of joint Markov blankets. It is shown that joint Markov blankets are a natural extension of Markov blankets, which are defined for single features, to a set of features. We show that these joint Markov blankets exist in feature sets consisting of the wavelet coefficients. Furthermore, we prove that wavelet energy features from the highest frequency resolution level form a joint Markov blanket for all other wavelet energy features. The joint Markov blanket theory indicates that one can expect an increase of classification accuracy with the increase of the frequency resolution level of the energy features.

Wavelet-Based Methodology for Evolutionary Spectra Estimation of Nonstationary Typhoon Processes

Directory of Open Access Journals (Sweden)

Guang-Dong Zhou

2015-01-01

Full Text Available Closed-form expressions are proposed to estimate the evolutionary power spectral density (EPSD of nonstationary typhoon processes by employing the wavelet transform. Relying on the definition of the EPSD and the concept of the wavelet transform, wavelet coefficients of a nonstationary typhoon process at a certain time instant are interpreted as the Fourier transform of a new nonstationary oscillatory process, whose modulating function is equal to the modulating function of the nonstationary typhoon process multiplied by the wavelet function in time domain. Then, the EPSD of nonstationary typhoon processes is deduced in a closed form and is formulated as a weighted sum of the squared moduli of time-dependent wavelet functions. The weighted coefficients are frequency-dependent functions defined by the wavelet coefficients of the nonstationary typhoon process and the overlapping area of two shifted wavelets. Compared with the EPSD, defined by a sum of the squared moduli of the wavelets in frequency domain in literature, this paper provides an EPSD estimation method in time domain. The theoretical results are verified by uniformly modulated nonstationary typhoon processes and non-uniformly modulated nonstationary typhoon processes.

Wavelet transform of generalized functions in K ′{Mp} spaces

Indian Academy of Sciences (India)

Using convolution theory in K{Mp} space we obtain bounded results for the wavelet transform. Calderón-type reproducing formula is derived in distribution sense as an application of the same. An inversion formula for the wavelet transform of generalized functions is established. Keywords. Continuous wavelet transform ...

Energy-Based Wavelet De-Noising of Hydrologic Time Series

Science.gov (United States)

Sang, Yan-Fang; Liu, Changming; Wang, Zhonggen; Wen, Jun; Shang, Lunyu

2014-01-01

De-noising is a substantial issue in hydrologic time series analysis, but it is a difficult task due to the defect of methods. In this paper an energy-based wavelet de-noising method was proposed. It is to remove noise by comparing energy distribution of series with the background energy distribution, which is established from Monte-Carlo test. Differing from wavelet threshold de-noising (WTD) method with the basis of wavelet coefficient thresholding, the proposed method is based on energy distribution of series. It can distinguish noise from deterministic components in series, and uncertainty of de-noising result can be quantitatively estimated using proper confidence interval, but WTD method cannot do this. Analysis of both synthetic and observed series verified the comparable power of the proposed method and WTD, but de-noising process by the former is more easily operable. The results also indicate the influences of three key factors (wavelet choice, decomposition level choice and noise content) on wavelet de-noising. Wavelet should be carefully chosen when using the proposed method. The suitable decomposition level for wavelet de-noising should correspond to series' deterministic sub-signal which has the smallest temporal scale. If too much noise is included in a series, accurate de-noising result cannot be obtained by the proposed method or WTD, but the series would show pure random but not autocorrelation characters, so de-noising is no longer needed. PMID:25360533

Architecture design of motion estimation for ITU-T H.263

Science.gov (United States)

Ku, Chung-Wei; Lin, Gong-Sheng; Chen, Liang-Gee; Lee, Yung-Ping

1997-01-01

Digitalized video and audio system has become the trend of the progress in multimedia, because it provides great performance in quality and feasibility of processing. However, as the huge amount of information is needed while the bandwidth is limitted, data compression plays an important role in the system. Say, for a 176 x 144 monochromic sequence with 10 frames/sec frame rate, the bandwidth is about 2Mbps. This wastes much channel resource and limits the applications. MPEG (moving picttre ezpert groip) standardizes the video codec scheme, and it performs high compression ratio while providing good quality. MPEG-i is used for the frame size about 352 x 240 and 30 frames per second, and MPEG-2 provides scalibility and can be applied on scenes with higher definition, say HDTV (high definition television). On the other hand, some applications concerns the very low bit-rate, such as videophone and video-conferencing. Because the channel bandwidth is much limitted in telephone network, a very high compression ratio must be required. ITU-T announced the H.263 video coding standards to meet the above requirements.8 According to the simulation results of TMN-5,22 it outperforms 11.263 with little overhead of complexity. Since wireless communication is the trend in the near future, low power design of the video codec is an important issue for portable visual telephone. Motion estimation is the most computation consuming parts in the whole video codec. About 60% of the computation is spent on this parts for the encoder. Several architectures were proposed for efficient processing of block matching algorithms. In this paper, in order to meet the requirements of 11.263 and the expectation of low power consumption, a modified sandwich architecture in21 is proposed. Based on the parallel processing philosophy, low power is expected and the generation of either one motion vector or four motion vectors with half-pixel accuracy is achieved concurrently. In addition, we will

Fundamental papers in wavelet theory

CERN Document Server

Walnut, David F

2006-01-01

This book traces the prehistory and initial development of wavelet theory, a discipline that has had a profound impact on mathematics, physics, and engineering. Interchanges between these fields during the last fifteen years have led to a number of advances in applications such as image compression, turbulence, machine vision, radar, and earthquake prediction. This book contains the seminal papers that presented the ideas from which wavelet theory evolved, as well as those major papers that developed the theory into its current form. These papers originated in a variety of journals from differ

On extensions of wavelet systems to dual pairs of frames

DEFF Research Database (Denmark)

Christensen, Ole; Kim, Hong Oh; Kim, Rae Young

2015-01-01

It is an open problem whether any pair of Bessel sequences with wavelet structure can be extended to a pair of dual frames by adding a pair of singly generated wavelet systems. We consider the particular case where the given wavelet systems are generated by the multiscale setup with trigonometric...

EEG Artifact Removal Using a Wavelet Neural Network

Science.gov (United States)

Nguyen, Hoang-Anh T.; Musson, John; Li, Jiang; McKenzie, Frederick; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

2011-01-01

!n this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We. compared the WNN algorithm with .the ICA technique ,and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.

Wavelets an elementary treatment of theory and applications

CERN Document Server

Koornwinder, T H

1993-01-01

Nowadays, some knowledge of wavelets is almost mandatory for mathematicians, physicists and electrical engineers. The emphasis in this volume, based on an intensive course on Wavelets given at CWI, Amsterdam, is on the affine case. The first part presents a concise introduction of the underlying theory to the uninitiated reader. The second part gives applications in various areas. Some of the contributions here are a fresh exposition of earlier work by others, while other papers contain new results by the authors. The areas are so diverse as seismic processing, quadrature formulae, and wavelet

Selection of the wavelet function for the frequencies estimation

International Nuclear Information System (INIS)

Garcia R, A.

2007-01-01

At the moment the signals are used to diagnose the state of the systems, by means of the extraction of their more important characteristics such as the frequencies, tendencies, changes and temporary evolutions. This characteristics are detected by means of diverse analysis techniques, as Autoregressive methods, Fourier Transformation, Fourier transformation in short time, Wavelet transformation, among others. The present work uses the one Wavelet transformation because it allows to analyze stationary, quasi-stationary and transitory signals in the time-frequency plane. It also describes a methodology to select the scales and the Wavelet function to be applied the one Wavelet transformation with the objective of detecting to the dominant system frequencies. (Author)

Wavelet Transforms: Application to Data Analysis - I -10 ...

Indian Academy of Sciences (India)

from 0 to 00, whereas translation index k takes values from -00 .... scaling function in any wavelet basis set. ..... sets derived from diverse sources like stock market, cos- ... [4] G B Folland, From Calculus to Wavelets: A New Mathematical Tech-.

Anisotropy in wavelet-based phase field models

KAUST Repository

Korzec, Maciek; Mü nch, Andreas; Sü li, Endre; Wagner, Barbara

2016-01-01

When describing the anisotropic evolution of microstructures in solids using phase-field models, the anisotropy of the crystalline phases is usually introduced into the interfacial energy by directional dependencies of the gradient energy coefficients. We consider an alternative approach based on a wavelet analogue of the Laplace operator that is intrinsically anisotropic and linear. The paper focuses on the classical coupled temperature/Ginzburg--Landau type phase-field model for dendritic growth. For the model based on the wavelet analogue, existence, uniqueness and continuous dependence on initial data are proved for weak solutions. Numerical studies of the wavelet based phase-field model show dendritic growth similar to the results obtained for classical phase-field models.

Anisotropy in wavelet-based phase field models

KAUST Repository

Korzec, Maciek

2016-04-01

When describing the anisotropic evolution of microstructures in solids using phase-field models, the anisotropy of the crystalline phases is usually introduced into the interfacial energy by directional dependencies of the gradient energy coefficients. We consider an alternative approach based on a wavelet analogue of the Laplace operator that is intrinsically anisotropic and linear. The paper focuses on the classical coupled temperature/Ginzburg--Landau type phase-field model for dendritic growth. For the model based on the wavelet analogue, existence, uniqueness and continuous dependence on initial data are proved for weak solutions. Numerical studies of the wavelet based phase-field model show dendritic growth similar to the results obtained for classical phase-field models.

Wavelet Analysis of Ultrasonic Echo Waveform and Application to Nondestructive Evaluation

International Nuclear Information System (INIS)

Park, Ik Keun; Park, Un Su; Ahn, Hyung Keun; Kwun, Sook In; Byeon, Jai Won

2000-01-01

Recently, advanced signal analysis which is called 'time-frequency analysis' has been used widely in nondestructive evaluation applications. Wavelet transform(WT) and Wigner Distribution are the most advanced techniques for processing signals with time-varying spectra. Wavelet analysis method is an attractive technique for evaluation of material characterization nondestructively. Wavelet transform is applied to the time-frequency analysis of ultrasonic echo waveform obtained by an ultrasonic pulse-echo technique. In this study, the feasibility of noise suppression of ultrasonic flaw signal and frequency-dependent ultrasonic group velocity and attenuation coefficient using wavelet analysis of ultrasonic echo waveform have been verified experimentally. The Gabor function is adopted the analyzing wavelet. The wavelet analysis shows that the variations of ultrasonic group velocity and attenuation coefficient due to the change of material characterization can be evaluated at each frequency. Furthermore, to assure the enhancement of detectability and new sizing performance, both computer simulated results and experimental measurements using wavelet signal processing are used to demonstrate the effectiveness of the noise suppression of ultrasonic flaw signal obtained from austenitic stainless steel weld including EDM notch

Islanding detection technique using wavelet energy in grid-connected PV system

Science.gov (United States)

Kim, Il Song

2016-08-01

This paper proposes a new islanding detection method using wavelet energy in a grid-connected photovoltaic system. The method detects spectral changes in the higher-frequency components of the point of common coupling voltage and obtains wavelet coefficients by multilevel wavelet analysis. The autocorrelation of the wavelet coefficients can clearly identify islanding detection, even in the variations of the grid voltage harmonics during normal operating conditions. The advantage of the proposed method is that it can detect islanding condition the conventional under voltage/over voltage/under frequency/over frequency methods fail to detect. The theoretical method to obtain wavelet energies is evolved and verified by the experimental result.

Wavelet neural networks with applications in financial engineering, chaos, and classification

CERN Document Server

Alexandridis, Antonios K

2014-01-01

Through extensive examples and case studies, Wavelet Neural Networks provides a step-by-step introduction to modeling, training, and forecasting using wavelet networks. The acclaimed authors present a statistical model identification framework to successfully apply wavelet networks in various applications, specifically, providing the mathematical and statistical framework needed for model selection, variable selection, wavelet network construction, initialization, training, forecasting and prediction, confidence intervals, prediction intervals, and model adequacy testing. The text is ideal for

2-Step scalar deadzone quantization for bitplane image coding.

Science.gov (United States)

Auli-Llinas, Francesc

2013-12-01

Modern lossy image coding systems generate a quality progressive codestream that, truncated at increasing rates, produces an image with decreasing distortion. Quality progressivity is commonly provided by an embedded quantizer that employs uniform scalar deadzone quantization (USDQ) together with a bitplane coding strategy. This paper introduces a 2-step scalar deadzone quantization (2SDQ) scheme that achieves same coding performance as that of USDQ while reducing the coding passes and the emitted symbols of the bitplane coding engine. This serves to reduce the computational costs of the codec and/or to code high dynamic range images. The main insights behind 2SDQ are the use of two quantization step sizes that approximate wavelet coefficients with more or less precision depending on their density, and a rate-distortion optimization technique that adjusts the distortion decreases produced when coding 2SDQ indexes. The integration of 2SDQ in current codecs is straightforward. The applicability and efficiency of 2SDQ are demonstrated within the framework of JPEG2000.

Regularization of EIT reconstruction based on multi-scales wavelet transforms

Directory of Open Access Journals (Sweden)

Gong Bo

2016-09-01

Full Text Available Electrical Impedance Tomography (EIT intends to obtain the conductivity distribution of a domain from the electrical boundary conditions. This is an ill-posed inverse problem usually solved on finite element meshes. Wavelet transforms are widely used for medical image reconstruction. However, because of the irregular form of the finite element meshes, the canonical wavelet transforms is impossible to perform on meshes. In this article, we present a framework that combines multi-scales wavelet transforms and finite element meshes by viewing meshes as undirected graphs and applying spectral graph wavelet transform on the meshes.

WAVELET ANALYSIS AND NEURAL NETWORK CLASSIFIERS TO DETECT MID-SAGITTAL SECTIONS FOR NUCHAL TRANSLUCENCY MEASUREMENT

Directory of Open Access Journals (Sweden)

Giuseppa Sciortino

2016-04-01

Full Text Available We propose a methodology to support the physician in the automatic identification of mid-sagittal sections of the fetus in ultrasound videos acquired during the first trimester of pregnancy. A good mid-sagittal section is a key requirement to make the correct measurement of nuchal translucency which is one of the main marker for screening of chromosomal defects such as trisomy 13, 18 and 21. NT measurement is beyond the scope of this article. The proposed methodology is mainly based on wavelet analysis and neural network classifiers to detect the jawbone and on radial symmetry analysis to detect the choroid plexus. Those steps allow to identify the frames which represent correct mid-sagittal sections to be processed. The performance of the proposed methodology was analyzed on 3000 random frames uniformly extracted from 10 real clinical ultrasound videos. With respect to a ground-truth provided by an expert physician, we obtained a true positive, a true negative and a balanced accuracy equal to 87.26%, 94.98% and 91.12% respectively.

Processing of pulse oximeter data using discrete wavelet analysis.

Science.gov (United States)

Lee, Seungjoon; Ibey, Bennett L; Xu, Weijian; Wilson, Mark A; Ericson, M Nance; Coté, Gerard L

2005-07-01

A wavelet-based signal processing technique was employed to improve an implantable blood perfusion monitoring system. Data was acquired from both in vitro and in vivo sources: a perfusion model and the proximal jejunum of an adult pig. Results showed that wavelet analysis could isolate perfusion signals from raw, periodic, in vitro data as well as fast Fourier transform (FFT) methods. However, for the quasi-periodic in vivo data segments, wavelet analysis provided more consistent results than the FFT analysis for data segments of 50, 10, and 5 s in length. Wavelet analysis has thus been shown to require less data points for quasi-periodic data than FFT analysis making it a good choice for an indwelling perfusion monitor where power consumption and reaction time are paramount.

Fast reversible wavelet image compressor

Science.gov (United States)

Kim, HyungJun; Li, Ching-Chung

1996-10-01

We present a unified image compressor with spline biorthogonal wavelets and dyadic rational filter coefficients which gives high computational speed and excellent compression performance. Convolutions with these filters can be preformed by using only arithmetic shifting and addition operations. Wavelet coefficients can be encoded with an arithmetic coder which also uses arithmetic shifting and addition operations. Therefore, from the beginning to the end, the while encoding/decoding process can be done within a short period of time. The proposed method naturally extends form the lossless compression to the lossy but high compression range and can be easily adapted to the progressive reconstruction.

The use of wavelet transforms in the solution of two-phase flow problems

International Nuclear Information System (INIS)

Moridis, G.J.; Nikolaou, M.; You, Yong

1994-10-01

In this paper we present the use of wavelets to solve the nonlinear Partial Differential.Equation (PDE) of two-phase flow in one dimension. The wavelet transforms allow a drastically different approach in the discretization of space. In contrast to the traditional trigonometric basis functions, wavelets approximate a function not by cancellation but by placement of wavelets at appropriate locations. When an abrupt chance, such as a shock wave or a spike, occurs in a function, only local coefficients in a wavelet approximation will be affected. The unique feature of wavelets is their Multi-Resolution Analysis (MRA) property, which allows seamless investigational any spatial resolution. The use of wavelets is tested in the solution of the one-dimensional Buckley-Leverett problem against analytical solutions and solutions obtained from standard numerical models. Two classes of wavelet bases (Daubechies and Chui-Wang) and two methods (Galerkin and collocation) are investigated. We determine that the Chui-Wang, wavelets and a collocation method provide the optimum wavelet solution for this type of problem. Increasing the resolution level improves the accuracy of the solution, but the order of the basis function seems to be far less important. Our results indicate that wavelet transforms are an effective and accurate method which does not suffer from oscillations or numerical smearing in the presence of steep fronts

Adaptive Filtering in the Wavelet Transform Domain via Genetic Algorithms

Science.gov (United States)

2004-08-06

wavelet transforms. Whereas the term “evolved” pertains only to the altered wavelet coefficients used during the inverse transform process. 2...words, the inverse transform produces the original signal x(t) from the wavelet and scaling coefficients. )()( ,, tdtx nk n nk k ψ...reconstruct the original signal as accurately as possible. The inverse transform reconstructs an approximation of the original signal (Burrus

Objective and subjective quality assessment of geometry compression of reconstructed 3D Humans in a 3D virtual room

NARCIS (Netherlands)

R.N. Mekuria (Rufael); P.S. Cesar Garcia (Pablo Santiago); A. Frisiello (Antonella); I. Doumanis (Ioannis)

2015-01-01

htmlabstractCompression of 3D object based video is relevant for 3D Immersive applications. Nevertheless, the perceptual aspects of the degradation introduced by codecs for meshes and point clouds are not well understood. In this paper we evaluate the subjective and objective degradations introduced

Multiresolution signal decomposition schemes. Part 2: Morphological wavelets

NARCIS (Netherlands)

H.J.A.M. Heijmans (Henk); J. Goutsias (John)

1999-01-01

htmlabstractIn its original form, the wavelet transform is a linear tool. However, it has been increasingly recognized that nonlinear extensions are possible. A major impulse to the development of nonlinear wavelet transforms has been given by the introduction of the lifting scheme by Sweldens. The

Wavelet modeling of signals for non-destructive testing of concretes

International Nuclear Information System (INIS)

Shao, Zhixue; Shi, Lihua; Cai, Jian

2011-01-01

In a non-destructive test of concrete structures, ultrasonic pulses are commonly used to detect damage or embedded objects from their reflections. A wavelet modeling method is proposed here to identify the main reflections and to remove the interferences in the detected ultrasonic waves. This method assumes that if the structure is stimulated by a wavelet function with good time–frequency localization ability, the detected signal is a combination of time-delayed and amplitude-attenuated wavelets. Therefore, modeling of the detected signal by wavelets can give a straightforward and simple model of the original signal. The central time and amplitude of each wavelet represent the position and amplitude of the reflections in the detected structure. A signal processing method is also proposed to estimate the structure response to wavelet excitation from its response to a high-voltage pulse with a sharp leading edge. A signal generation card with a compact peripheral component interconnect extension for instrumentation interface is designed to produce this high-voltage pulse. The proposed method is applied to synthesized aperture focusing technology of concrete specimens and the image results are provided

Characterization and Simulation of Gunfire with Wavelets

Directory of Open Access Journals (Sweden)

David O. Smallwood

1999-01-01

Full Text Available Gunfire is used as an example to show how the wavelet transform can be used to characterize and simulate nonstationary random events when an ensemble of events is available. The structural response to nearby firing of a high-firing rate gun has been characterized in several ways as a nonstationary random process. The current paper will explore a method to describe the nonstationary random process using a wavelet transform. The gunfire record is broken up into a sequence of transient waveforms each representing the response to the firing of a single round. A wavelet transform is performed on each of these records. The gunfire is simulated by generating realizations of records of a single-round firing by computing an inverse wavelet transform from Gaussian random coefficients with the same mean and standard deviation as those estimated from the previously analyzed gunfire record. The individual records are assembled into a realization of many rounds firing. A second-order correction of the probability density function is accomplished with a zero memory nonlinear function. The method is straightforward, easy to implement, and produces a simulated record much like the measured gunfire record.

Video Multiple Watermarking Technique Based on Image Interlacing Using DWT

Directory of Open Access Journals (Sweden)

Mohamed M. Ibrahim

2014-01-01

Full Text Available Digital watermarking is one of the important techniques to secure digital media files in the domains of data authentication and copyright protection. In the nonblind watermarking systems, the need of the original host file in the watermark recovery operation makes an overhead over the system resources, doubles memory capacity, and doubles communications bandwidth. In this paper, a robust video multiple watermarking technique is proposed to solve this problem. This technique is based on image interlacing. In this technique, three-level discrete wavelet transform (DWT is used as a watermark embedding/extracting domain, Arnold transform is used as a watermark encryption/decryption method, and different types of media (gray image, color image, and video are used as watermarks. The robustness of this technique is tested by applying different types of attacks such as: geometric, noising, format-compression, and image-processing attacks. The simulation results show the effectiveness and good performance of the proposed technique in saving system resources, memory capacity, and communications bandwidth.

Video multiple watermarking technique based on image interlacing using DWT.

Science.gov (United States)

Ibrahim, Mohamed M; Abdel Kader, Neamat S; Zorkany, M

2014-01-01

Digital watermarking is one of the important techniques to secure digital media files in the domains of data authentication and copyright protection. In the nonblind watermarking systems, the need of the original host file in the watermark recovery operation makes an overhead over the system resources, doubles memory capacity, and doubles communications bandwidth. In this paper, a robust video multiple watermarking technique is proposed to solve this problem. This technique is based on image interlacing. In this technique, three-level discrete wavelet transform (DWT) is used as a watermark embedding/extracting domain, Arnold transform is used as a watermark encryption/decryption method, and different types of media (gray image, color image, and video) are used as watermarks. The robustness of this technique is tested by applying different types of attacks such as: geometric, noising, format-compression, and image-processing attacks. The simulation results show the effectiveness and good performance of the proposed technique in saving system resources, memory capacity, and communications bandwidth.

Watermarking on 3D mesh based on spherical wavelet transform.

Science.gov (United States)

Jin, Jian-Qiu; Dai, Min-Ya; Bao, Hu-Jun; Peng, Qun-Sheng

2004-03-01

In this paper we propose a robust watermarking algorithm for 3D mesh. The algorithm is based on spherical wavelet transform. Our basic idea is to decompose the original mesh into a series of details at different scales by using spherical wavelet transform; the watermark is then embedded into the different levels of details. The embedding process includes: global sphere parameterization, spherical uniform sampling, spherical wavelet forward transform, embedding watermark, spherical wavelet inverse transform, and at last resampling the mesh watermarked to recover the topological connectivity of the original model. Experiments showed that our algorithm can improve the capacity of the watermark and the robustness of watermarking against attacks.

Constructing New Biorthogonal Wavelet Type which Matched for Extracting the Iris Image Features

International Nuclear Information System (INIS)

Isnanto, R Rizal; Suhardjo; Susanto, Adhi

2013-01-01

Some former research have been made for obtaining a new type of wavelet. In case of iris recognition using orthogonal or biorthogonal wavelets, it had been obtained that Haar filter is most suitable to recognize the iris image. However, designing the new wavelet should be done to find a most matched wavelet to extract the iris image features, for which we can easily apply it for identification, recognition, or authentication purposes. In this research, a new biorthogonal wavelet was designed based on Haar filter properties and Haar's orthogonality conditions. As result, it can be obtained a new biorthogonal 5/7 filter type wavelet which has a better than other types of wavelets, including Haar, to extract the iris image features based on its mean-squared error (MSE) and Euclidean distance parameters.

Dual-tree complex wavelet for medical image watermarking

International Nuclear Information System (INIS)

Mavudila, K.R.; Ndaye, B.M.; Masmoudi, L.; Hassanain, N.; Cherkaoui, M.

2010-01-01

In order to transmit medical data between hospitals, we insert the information for each patient in the image and its diagnosis, the watermarking consist to insert a message in the image and try to find it with the maximum possible fidelity. This paper presents a blind watermarking scheme in wavelet transform domain dual tree (DTT), who increasing the robustness and preserves the image quality. This system is transparent to the user and allows image integrity control. In addition, it provides information on the location of potential alterations and an evaluation of image modifications which is of major importance in a medico-legal framework. An example using head magnetic resonance and mammography imaging illustrates the overall method. Wavelet techniques can be successfully applied in various image processing methods, namely in image de noising, segmentation, classification, watermarking and others. In this paper we discussed the application of dual tree complex wavelet transform (D T-CWT), which has significant advantages over classic discrete wavelet transform (DWT), for certain image processing problems. The D T-CWT is a form of discreet wavelet transform which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The main part of the paper is devoted to profit the exceptional quality for D T-CWT, compared to classical DWT, for a blind medical image watermarking, our schemes are using for the performance bivariate shrinkage with local variance estimation and are robust of attacks and favourably preserves the visual quality. Experimental results show that embedded watermarks using CWT give good image quality and are robust in comparison with the classical DWT.

Schrödinger like equation for wavelets

Directory of Open Access Journals (Sweden)

A. Zúñiga-Segundo

2016-01-01

Full Text Available An explicit phase space representation of the wave function is build based on a wavelet transformation. The wavelet transformation allows us to understand the relationship between s − ordered Wigner function, (or Wigner function when s = 0, and the Torres-Vega-Frederick’s wave functions. This relationship is necessary to find a general solution of the Schrödinger equation in phase-space.

Thin film description by wavelet coefficients statistics

Czech Academy of Sciences Publication Activity Database

Boldyš, Jiří; Hrach, R.

2005-01-01

Roč. 55, č. 1 (2005), s. 55-64 ISSN 0011-4626 Grant - others:GA UK(CZ) 173/2003 Institutional research plan: CEZ:AV0Z10750506 Keywords : thin films * wavelet transform * descriptors * histogram model Subject RIV: BD - Theory of Information Impact factor: 0.360, year: 2005 http://library.utia.cas.cz/separaty/2009/ZOI/boldys-thin film description by wavelet coefficients statistics .pdf

The De-Noising of Sonic Echo Test Data through Wavelet Transform Reconstruction

Directory of Open Access Journals (Sweden)

J.N. Watson

1999-01-01

Full Text Available This paper presents the results of feasibility study into the application of the wavelet transform signal processing method to sonic based non-destructive testing techniques. Finite element generated data from cast in situ foundation piles were collated and processed using both continuous and discrete wavelet transform techniques. Results were compared with conventional Fourier based methods. The discrete Daubechies wavelets and the continuous Mexican hat wavelet were used and their relative merits investigated. It was found that both the continuous Mexican hat and discrete Daubechies D8 wavelets were significantly better at locating the pile toe compared than the Fourier filtered case. The wavelet transform method was then applied to field test data and found to be successful in facilitating the detection of the pile toe.

Processors for wavelet analysis and synthesis: NIFS and TI-C80 MVP

Science.gov (United States)

Brooks, Geoffrey W.

1996-03-01

Two processors are considered for image quadrature mirror filtering (QMF). The neuromorphic infrared focal-plane sensor (NIFS) is an existing prototype analog processor offering high speed spatio-temporal Gaussian filtering, which could be used for the QMF low- pass function, and difference of Gaussian filtering, which could be used for the QMF high- pass function. Although not designed specifically for wavelet analysis, the biologically- inspired system accomplishes the most computationally intensive part of QMF processing. The Texas Instruments (TI) TMS320C80 Multimedia Video Processor (MVP) is a 32-bit RISC master processor with four advanced digital signal processors (DSPs) on a single chip. Algorithm partitioning, memory management and other issues are considered for optimal performance. This paper presents these considerations with simulated results leading to processor implementation of high-speed QMF analysis and synthesis.

Wavelet Based Diagnosis and Protection of Electric Motors

OpenAIRE

Khan, M. Abdesh Shafiel Kafiey; Rahman, M. Azizur

2010-01-01

In this chapter, a short review of conventional Fourier transforms and new wavelet based faults diagnostic and protection techniques for electric motors is presented. The new hybrid wavelet packet transform (WPT) and neural network (NN) based faults diagnostic algorithm is developed and implemented for electric motors. The proposed WPT and NN

Evaluation of the wavelet image two-line coder

DEFF Research Database (Denmark)

Rein, Stephan Alexander; Fitzek, Frank Hanns Paul; Gühmann, Clemens

2015-01-01

This paper introduces the wavelet image two-line (Wi2l) coding algorithm for low complexity compression of images. The algorithm recursively encodes an image backwards reading only two lines of a wavelet subband, which are read in blocks of 512 bytes from flash memory. It thus only requires very ...

Improvement of electrocardiogram by empirical wavelet transform

Science.gov (United States)

Chanchang, Vikanda; Kumchaiseemak, Nakorn; Sutthiopad, Malee; Luengviriya, Chaiya

2017-09-01

Electrocardiogram (ECG) is a crucial tool in the detection of cardiac arrhythmia. It is also often used in a routine physical exam, especially, for elderly people. This graphical representation of electrical activity of heart is obtained by a measurement of voltage at the skin; therefore, the signal is always contaminated by noise from various sources. For a proper interpretation, the quality of the ECG should be improved by a noise reduction. In this article, we present a study of a noise filtration in the ECG by using an empirical wavelet transform (EWT). Unlike the traditional wavelet method, EWT is adaptive since the frequency spectrum of the ECG is taken into account in the construction of the wavelet basis. We show that the signal-to-noise ratio increases after the noise filtration for different noise artefacts.

Multiresolution wavelet-ANN model for significant wave height forecasting.

Digital Repository Service at National Institute of Oceanography (India)

Deka, P.C.; Mandal, S.; Prahlada, R.

Hybrid wavelet artificial neural network (WLNN) has been applied in the present study to forecast significant wave heights (Hs). Here Discrete Wavelet Transformation is used to preprocess the time series data (Hs) prior to Artificial Neural Network...

A CMOS Morlet Wavelet Generator

Directory of Open Access Journals (Sweden)

A. I. Bautista-Castillo

2017-04-01

Full Text Available The design and characterization of a CMOS circuit for Morlet wavelet generation is introduced. With the proposed Morlet wavelet circuit, it is possible to reach a~low power consumption, improve standard deviation (σ control and also have a small form factor. A prototype in a double poly, three metal layers, 0.5 µm CMOS process from MOSIS foundry was carried out in order to verify the functionality of the proposal. However, the design methodology can be extended to different CMOS processes. According to the performance exhibited by the circuit, may be useful in many different signal processing tasks such as nonlinear time-variant systems.

Generalized Wavelet Fisher’s Information of 1/fα Signals

Directory of Open Access Journals (Sweden)

Julio Ramírez-Pacheco

2015-01-01

Full Text Available This paper defines the generalized wavelet Fisher information of parameter q. This information measure is obtained by generalizing the time-domain definition of Fisher’s information of Furuichi to the wavelet domain and allows to quantify smoothness and correlation, among other signals characteristics. Closed-form expressions of generalized wavelet Fisher information for 1/fα signals are determined and a detailed discussion of their properties, characteristics and their relationship with wavelet q-Fisher information are given. Information planes of 1/f signals Fisher information are obtained and, based on these, potential applications are highlighted. Finally, generalized wavelet Fisher information is applied to the problem of detecting and locating weak structural breaks in stationary 1/f signals, particularly for fractional Gaussian noise series. It is shown that by using a joint Fisher/F-Statistic procedure, significant improvements in time and accuracy are achieved in comparison with the sole application of the F-statistic.

A novel neural-wavelet approach for process diagnostics and complex system modeling

Science.gov (United States)

Gao, Rong

Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

Psychovisual masks and intelligent streaming RTP techniques for the MPEG-4 standard

Science.gov (United States)

Mecocci, Alessandro; Falconi, Francesco

2003-06-01

like: DivX, Xvid, and Cisco"s Mpeg-4IP, have been analyzed but, as for today, they do not support VO). The original code has been deeply modified to integrate the SLIC and to adapt it for real-time streaming. A personal RTP (Real Time Protocol) has been defined and a Client-Server application has been developed. The viewer can decode and demultiplex the stream in real-time, while adapting to the changing modalities adopted by the Server according to the current video content. The proposed codec works as follows: the image background is separated by means of a segmentation module and it is transmitted by means of a wavelet compression scheme similar to that used in the JPEG2000. The VO are coded separately and multiplexed with the background stream. At the receiver the stream is demultiplexed to obtain the background and the VO that are subsequently pasted together. The final quality depends on many factors, in particular: the quantization parameters, the Group Of Video Object (GOV) length, the GOV structure (i.e. the number of I-P-B VOP), the search area for motion compensation. These factors are strongly related to the following measurement parameters (that have been defined during the development): the Objects Apparent Size (OAS) in the scene, the Video Object Incidence factor (VOI), the temporal correlation (measured through the Normalized Mean SAD, NMSAD). The SLIC module analyzes the currently transmitted video and selects the most appropriate settings by choosing from a predefined set of transmission modalities. For example, in the case of a highly temporal correlated sequence, the number of B-VOP is increased to improve the compression ratio. The strategy for the selection of the number of B-VOP turns out to be very different from those reported in the literature for B-frames (adopted for MPEG-1 and MPEG-2), due to the different behaviour of the temporal correlation when limited only to moving objects. The SLIC module also decides how to transmit the background

Application of Cubic Box Spline Wavelets in the Analysis of Signal Singularities

Directory of Open Access Journals (Sweden)

Rakowski Waldemar

2015-12-01

Full Text Available In the subject literature, wavelets such as the Mexican hat (the second derivative of a Gaussian or the quadratic box spline are commonly used for the task of singularity detection. The disadvantage of the Mexican hat, however, is its unlimited support; the disadvantage of the quadratic box spline is a phase shift introduced by the wavelet, making it difficult to locate singular points. The paper deals with the construction and properties of wavelets in the form of cubic box splines which have compact and short support and which do not introduce a phase shift. The digital filters associated with cubic box wavelets that are applied in implementing the discrete dyadic wavelet transform are defined. The filters and the algorithme à trous of the discrete dyadic wavelet transform are used in detecting signal singularities and in calculating the measures of signal singularities in the form of a Lipschitz exponent. The article presents examples illustrating the use of cubic box spline wavelets in the analysis of signal singularities.

Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation

Directory of Open Access Journals (Sweden)

Schell Thomas

2003-01-01

Full Text Available In image compression, the wavelet transformation is a state-of-the-art component. Recently, wavelet packet decomposition has received quite an interest. A popular approach for wavelet packet decomposition is the near-best-basis algorithm using nonadditive cost functions. In contrast to additive cost functions, the wavelet packet decomposition of the near-best-basis algorithm is only suboptimal. We apply methods from the field of evolutionary computation (EC to test the quality of the near-best-basis results. We observe a phenomenon: the results of the near-best-basis algorithm are inferior in terms of cost-function optimization but are superior in terms of rate/distortion performance compared to EC methods.

Non-stationary dynamics in the bouncing ball: A wavelet perspective

Energy Technology Data Exchange (ETDEWEB)

Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in [Department of Physical Sciences, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur 741246 (India); Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in [Plasma Physics Division, Saha Institute of Nuclear Physics (SINP), Sector 1, Block-AF, Bidhannagar, Kolkata 700064 (India)

2014-12-01

The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding to neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.

Wavelet entropy of BOLD time series: An application to Rolandic epilepsy.

Science.gov (United States)

Gupta, Lalit; Jansen, Jacobus F A; Hofman, Paul A M; Besseling, René M H; de Louw, Anton J A; Aldenkamp, Albert P; Backes, Walter H

2017-12-01

To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence ( T2*-weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy. Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences. The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls. 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1728-1737. © 2017 International Society for Magnetic

WAVELET-BASED ALGORITHM FOR DETECTION OF BEARING FAULTS IN A GAS TURBINE ENGINE

Directory of Open Access Journals (Sweden)

Sergiy Enchev

2014-07-01

Full Text Available Presented is a gas turbine engine bearing diagnostic system that integrates information from various advanced vibration analysis techniques to achieve robust bearing health state awareness. This paper presents a computational algorithm for identifying power frequency variations and integer harmonics by using wavelet-based transform. The continuous wavelet transform with  the complex Morlet wavelet is adopted to detect the harmonics presented in a power signal. The algorithm based on the discrete stationary wavelet transform is adopted to denoise the wavelet ridges.

Polarized spectral features of human breast tissues through wavelet ...

Indian Academy of Sciences (India)

Abstract. Fluorescence characteristics of human breast tissues are investigated through wavelet transform and principal component analysis (PCA). Wavelet transform of polar- ized fluorescence spectra of human breast tissues is found to localize spectral features that can reliably differentiate different tissue types.

A Wavelet-Based Approach to Fall Detection

Directory of Open Access Journals (Sweden)

Luca Palmerini

2015-05-01

Full Text Available Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim of this work is to present a novel wavelet-based approach to fall detection, focusing on the impact phase and using a dataset of real-world falls. Since recorded falls result in a non-stationary signal, a wavelet transform was chosen to examine fall patterns. The idea is to consider the average fall pattern as the “prototype fall”.In order to detect falls, every acceleration signal can be compared to this prototype through wavelet analysis. The similarity of the recorded signal with the prototype fall is a feature that can be used in order to determine the difference between falls and daily activities. The discriminative ability of this feature is evaluated on real-world data. It outperforms other features that are commonly used in fall detection studies, with an Area Under the Curve of 0.918. This result suggests that the proposed wavelet-based feature is promising and future studies could use this feature (in combination with others considering different fall phases in order to improve the performance of fall detection algorithms.

A note on the standard dual frame of a wavelet frame with three-scale

International Nuclear Information System (INIS)

Chen Qingjiang; Wei Zongtian; Feng Jinshun

2009-01-01

In this paper, it is shown that there exist wavelet frames generated by two functions which have good dual wavelet frames, but for which the standard dual wavelet frame does not consist of wavelets. That is to say, the standard dual wavelet frame cannot be generated by the translations and dilations of a single function. Relation to some physical theories such as entropy and E-infinity theory is also discussed.

Construction and decomposition of biorthogonal vector-valued wavelets with compact support

International Nuclear Information System (INIS)

Chen Qingjiang; Cao Huaixin; Shi Zhi

2009-01-01

In this article, we introduce vector-valued multiresolution analysis and the biorthogonal vector-valued wavelets with four-scale. The existence of a class of biorthogonal vector-valued wavelets with compact support associated with a pair of biorthogonal vector-valued scaling functions with compact support is discussed. A method for designing a class of biorthogonal compactly supported vector-valued wavelets with four-scale is proposed by virtue of multiresolution analysis and matrix theory. The biorthogonality properties concerning vector-valued wavelet packets are characterized with the aid of time-frequency analysis method and operator theory. Three biorthogonality formulas regarding them are presented.

Research on fault diagnosis for RCP rotor based on wavelet analysis

International Nuclear Information System (INIS)

Chen Zhihui; Xia Hong; Wang Taotao

2008-01-01

Wavelet analysis is with the characteristics of noise reduction and multiscale resolution, and can be used to effectively extract the fault features of the typical failures of the main pumps. Simulink is used to simulate the typical faults: Misalignment Fault, Crackle Fault of rotor, and Initial Bending Fault, then the Wavelet method is used to analyze the vibration signal. The result shows that the extracted fault feature from wavelet analysis can effectively identify the fault signals. The Wavelet analysis is a practical method for the diagnosis of main coolant pump failure, and is with certain value for application and significance. (authors)

Study of Denoising in TEOAE Signals Using an Appropriate Mother Wavelet Function

Directory of Open Access Journals (Sweden)

Habib Alizadeh Dizaji

2007-06-01

Full Text Available Background and Aim: Matching a mother wavelet to class of signals can be of interest in signal analy­sis and denoising based on wavelet multiresolution analysis and decomposition. As transient evoked otoacoustic emissions (TEOAES are contaminated with noise, the aim of this work was to pro­vide a quantitative approach to the problem of matching a mother wavelet to TEOAE signals by us­ing tun­ing curves and to use it for analysis and denoising TEOAE signals. Approximated mother wave­let for TEOAE signals was calculated using an algorithm for designing wavelet to match a specified sig­nal.Materials and Methods: In this paper a tuning curve has used as a template for designing a mother wave­let that has maximum matching to the tuning curve. The mother wavelet matching was performed on tuning curves spectrum magnitude and phase independent of one another. The scaling function was calcu­lated from the matched mother wavelet and by using these functions, lowpass and highpass filters were designed for a filter bank and otoacoustic emissions signal analysis and synthesis. After signal analyz­ing, denoising was performed by time windowing the signal time-frequency component.Results: Aanalysis indicated more signal reconstruction improvement in comparison with coiflets mother wavelet and by using the purposed denoising algorithm it is possible to enhance signal to noise ra­tio up to dB.Conclusion: The wavelet generated from this algorithm was remarkably similar to the biorthogonal wave­lets. Therefore, by matching a biorthogonal wavelet to the tuning curve and using wavelet packet analy­sis, a high resolution time-frequency analysis for the otoacoustic emission signals is possible.

Optimization design of biorthogonal wavelets for embedded image coding

NARCIS (Netherlands)

Lin, Z.; Zheng, N.; Liu, Y.; Wetering, van de H.M.M.

2007-01-01

We present here a simple technique for parametrization of popular biorthogonal wavelet filter banks (BWFBs) having vanishing moments (VMs) of arbitrary multiplicity. Given a prime wavelet filter with VMs of arbitrary multiplicity, after formulating it as a trigonometric polynomial depending on two

On Parseval Wavelet Frames with Two or Three Generators via the Unitary Extension Principle

DEFF Research Database (Denmark)

Christensen, Ole; Kim, Hong Oh; Kim, Rae Young

2014-01-01

The unitary extension principle (UEP) by A. Ron and Z. Shen yields a sufficient condition for the construction of Parseval wavelet frames with multiple generators. In this paper we characterize the UEP-type wavelet systems that can be extended to a Parseval wavelet frame by adding just one UEP......-type wavelet system. We derive a condition that is necessary for the extension of a UEP-type wavelet system to any Parseval wavelet frame with any number of generators and prove that this condition is also sufficient to ensure that an extension with just two generators is possible....

Analysis and removing noise from speech using wavelet transform

Science.gov (United States)

Tomala, Karel; Voznak, Miroslav; Partila, Pavol; Rezac, Filip; Safarik, Jakub

2013-05-01

The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked as telecommunication providers often focus on increasing network capacity, expansion of services offered and their enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice which was distorted by Gaussian white noise. An evaluation of the impact on speech quality was carried out by an intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples.

Wavelet denoising method; application to the flow rate estimation for water level control

International Nuclear Information System (INIS)

Park, Gee Young; Park, Jin Ho; Lee, Jung Han; Kim, Bong Soo; Seong, Poong Hyun

2003-01-01

The wavelet transform decomposes a signal into time- and frequency-domain signals and it is well known that a noise-corrupted signal could be reconstructed or estimated when a proper denoising method is involved in the wavelet transform. Among the wavelet denoising methods proposed up to now, the wavelets by Mallat and Zhong can reconstruct best the pure transient signal from a highly corrupted signal. But there has been no systematic way of discriminating the original signal from the noise in a dyadic wavelet transform. In this paper, a systematic method is proposed for noise discrimination, which could be implemented easily into a digital system. For demonstrating the potential role of the wavelet denoising method in the nuclear field, this method is applied to the steam or feedwater flow rate estimation of the secondary loop. And the configuration of the S/G water level control system is proposed for incorporating the wavelet denoising method in estimating the flow rate value at low operating powers

ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit

Directory of Open Access Journals (Sweden)

Zhihuai Xiao

2015-01-01

Full Text Available Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO- initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the frequency components of the hydroturbine generating unit vibration signals are used as feature vectors for wavelet neural network training to realize mapping relationship from vibration features to fault types. A real vibration fault diagnosis case result of a hydroturbine generating unit shows that the proposed method has faster convergence speed and stronger generalization ability than the traditional wavelet neural network and ACO wavelet neural network. Thus it can provide an effective solution for online vibration fault diagnosis of a hydroturbine generating unit.

Determination of phase from the ridge of CWT using generalized Morse wavelet

Science.gov (United States)

Kocahan, Ozlem; Tiryaki, Erhan; Coskun, Emre; Ozder, Serhat

2018-03-01

The selection of wavelet is an important step in order to determine the phase from the fringe patterns. In the present work, a new wavelet for phase retrieval from the ridge of continuous wavelet transform (CWT) is presented. The phase distributions have been extracted from the optical fringe pattern by choosing the zero order generalized morse wavelet (GMW) as a mother wavelet. The aim of the study is to reveal the ways in which the two varying parameters of GMW affect the phase calculation. To show the validity of this method, an experimental study has been conducted by using the diffraction phase microscopy (DPM) setup; consequently, the profiles of red blood cells have been retrieved. The results for the CWT ridge technique with GMW have been compared with the results for the Morlet wavelet and the Paul wavelet; the results are almost identical for Paul and zero order GMW because of their degree of freedom. Also, for further discussion, the Fourier transform and the Stockwell transform have been applied comparatively. The outcome of the comparison reveals that GMWs are highly applicable to the research in various areas, predominantly biomedicine.

Near-Horizontal, Two-Phase Flow Patterns of Nitrogen and Hydrogen at Low Mass Heat and Flux Supplement

Science.gov (United States)

VanDresar, Neil T.; Siegwarth, James D.

2001-01-01

This CD is a companion to NASA/TP-2001-210380. It contains digitized movies of particular flow patterns observed in experimental work. The movies have been provided in QuickTime format, encoded at 320w x 240h pixels, 15 fps, using the Sorenson Video Codec for compression.

Stochastic Packet Loss Model to Evaluate QoE Impairments

Science.gov (United States)

Hohlfeld, Oliver

With provisioning of broadband access for mass market—even in wireless and mobile networks—multimedia content, especially real-time streaming of high-quality audio and video, is extensively viewed and exchanged over the Internet. Quality of Experience (QoE) aspects, describing the service quality perceived by the user, is a vital factor in ensuring customer satisfaction in today's communication networks. Frameworks for accessing quality degradations in streamed video currently are investigated as a complex multi-layered research topic, involving network traffic load, codec functions and measures of user perception of video quality.

Fringe pattern information retrieval using wavelets

Science.gov (United States)

Sciammarella, Cesar A.; Patimo, Caterina; Manicone, Pasquale D.; Lamberti, Luciano

2005-08-01

Two-dimensional phase modulation is currently the basic model used in the interpretation of fringe patterns that contain displacement information, moire, holographic interferometry, speckle techniques. Another way to look to these two-dimensional signals is to consider them as frequency modulated signals. This alternative interpretation has practical implications similar to those that exist in radio engineering for handling frequency modulated signals. Utilizing this model it is possible to obtain frequency information by using the energy approach introduced by Ville in 1944. A natural complementary tool of this process is the wavelet methodology. The use of wavelet makes it possible to obtain the local values of the frequency in a one or two dimensional domain without the need of previous phase retrieval and differentiation. Furthermore from the properties of wavelets it is also possible to obtain at the same time the phase of the signal with the advantage of a better noise removal capabilities and the possibility of developing simpler algorithms for phase unwrapping due to the availability of the derivative of the phase.

Wavelet-based compression of pathological images for telemedicine applications

Science.gov (United States)

Chen, Chang W.; Jiang, Jianfei; Zheng, Zhiyong; Wu, Xue G.; Yu, Lun

2000-05-01

In this paper, we present the performance evaluation of wavelet-based coding techniques as applied to the compression of pathological images for application in an Internet-based telemedicine system. We first study how well suited the wavelet-based coding is as it applies to the compression of pathological images, since these images often contain fine textures that are often critical to the diagnosis of potential diseases. We compare the wavelet-based compression with the DCT-based JPEG compression in the DICOM standard for medical imaging applications. Both objective and subjective measures have been studied in the evaluation of compression performance. These studies are performed in close collaboration with expert pathologists who have conducted the evaluation of the compressed pathological images and communication engineers and information scientists who designed the proposed telemedicine system. These performance evaluations have shown that the wavelet-based coding is suitable for the compression of various pathological images and can be integrated well with the Internet-based telemedicine systems. A prototype of the proposed telemedicine system has been developed in which the wavelet-based coding is adopted for the compression to achieve bandwidth efficient transmission and therefore speed up the communications between the remote terminal and the central server of the telemedicine system.

Using the Dual-Tree Complex Wavelet Transform for Improved Fabric Defect Detection

Directory of Open Access Journals (Sweden)

Hermanus Vermaak

2016-01-01

Full Text Available The dual-tree complex wavelet transform (DTCWT solves the problems of shift variance and low directional selectivity in two and higher dimensions found with the commonly used discrete wavelet transform (DWT. It has been proposed for applications such as texture classification and content-based image retrieval. In this paper, the performance of the dual-tree complex wavelet transform for fabric defect detection is evaluated. As experimental samples, the fabric images from TILDA, a textile texture database from the Workgroup on Texture Analysis of the German Research Council (DFG, are used. The mean energies of real and imaginary parts of complex wavelet coefficients taken separately are identified as effective features for the purpose of fabric defect detection. Then it is shown that the use of the dual-tree complex wavelet transform yields greater performance as compared to the undecimated wavelet transform (UDWT with a detection rate of 4.5% to 15.8% higher depending on the fabric type.

Auditory ERB like admissible wavelet packet features for TIMIT phoneme recognition

Directory of Open Access Journals (Sweden)

P.K. Sahu

2014-09-01

Full Text Available In recent years wavelet transform has been found to be an effective tool for time–frequency analysis. Wavelet transform has been used as feature extraction in speech recognition applications and it has proved to be an effective technique for unvoiced phoneme classification. In this paper a new filter structure using admissible wavelet packet is analyzed for English phoneme recognition. These filters have the benefit of having frequency bands spacing similar to the auditory Equivalent Rectangular Bandwidth (ERB scale. Central frequencies of ERB scale are equally distributed along the frequency response of human cochlea. A new sets of features are derived using wavelet packet transform's multi-resolution capabilities and found to be better than conventional features for unvoiced phoneme problems. Some of the noises from NOISEX-92 database has been used for preparing the artificial noisy database to test the robustness of wavelet based features.

Wavelet-Coded OFDM for Next Generation Mobile Communications

DEFF Research Database (Denmark)

Cavalcante, Lucas Costa Pereira; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso

2016-01-01

In this work, we evaluate the performance of Wavelet-Coding into offering robustness for OFDM signals against the combined effects of varying fading and noise bursts. Wavelet-Code enables high diversity gains with a low complex receiver, and, most notably, without compromising the system’s spectr......-wave frequencies in future generation mobile communication due to its robustness against multipath fading....

Evolutive Optimization of Wavelets and Shapelets for Bioelectrical Signal Analysis

OpenAIRE

Pinzón Morales, Rubén Dario

2011-01-01

análisis Wavelet es una poderosa herramienta para el procesamiento de señal digital. Ha sido ampliamente utilizado en señales bioeléctricas incluyendo evocar potenciales relacionados (ERP), señales de electromiografía (EMG), grabaciones de microelectrodos (MER), electrocardiograma (ECG), electroencefalogramas (EEG), entre otros. Algunas de las principales ventajas de la wavelet transform son el soporte compacto, y la concentración de la energía. Básicamente, la transformada wavelet es una con...

Multiscale peak detection in wavelet space.

Science.gov (United States)

Zhang, Zhi-Min; Tong, Xia; Peng, Ying; Ma, Pan; Zhang, Ming-Jin; Lu, Hong-Mei; Chen, Xiao-Qing; Liang, Yi-Zeng

2015-12-07

Accurate peak detection is essential for analyzing high-throughput datasets generated by analytical instruments. Derivatives with noise reduction and matched filtration are frequently used, but they are sensitive to baseline variations, random noise and deviations in the peak shape. A continuous wavelet transform (CWT)-based method is more practical and popular in this situation, which can increase the accuracy and reliability by identifying peaks across scales in wavelet space and implicitly removing noise as well as the baseline. However, its computational load is relatively high and the estimated features of peaks may not be accurate in the case of peaks that are overlapping, dense or weak. In this study, we present multi-scale peak detection (MSPD) by taking full advantage of additional information in wavelet space including ridges, valleys, and zero-crossings. It can achieve a high accuracy by thresholding each detected peak with the maximum of its ridge. It has been comprehensively evaluated with MALDI-TOF spectra in proteomics, the CAMDA 2006 SELDI dataset as well as the Romanian database of Raman spectra, which is particularly suitable for detecting peaks in high-throughput analytical signals. Receiver operating characteristic (ROC) curves show that MSPD can detect more true peaks while keeping the false discovery rate lower than MassSpecWavelet and MALDIquant methods. Superior results in Raman spectra suggest that MSPD seems to be a more universal method for peak detection. MSPD has been designed and implemented efficiently in Python and Cython. It is available as an open source package at .

Partially coherent imaging and spatial coherence wavelets

International Nuclear Information System (INIS)

Castaneda, Roman

2003-03-01

A description of spatially partially coherent imaging based on the propagation of second order spatial coherence wavelets and marginal power spectra (Wigner distribution functions) is presented. In this dynamics, the spatial coherence wavelets will be affected by the system through its elementary transfer function. The consistency of the model with the both extreme cases of full coherent and incoherent imaging was proved. In the last case we obtained the classical concept of optical transfer function as a simple integral of the elementary transfer function. Furthermore, the elementary incoherent response function was introduced as the Fourier transform of the elementary transfer function. It describes the propagation of spatial coherence wavelets form each object point to each image point through a specific point on the pupil planes. The point spread function of the system was obtained by a simple integral of the elementary incoherent response function. (author)

Wavelet theory and belt finishing process, influence of wavelet shape on the surface roughness parameter values

International Nuclear Information System (INIS)

Khawaja, Z; Mazeran, P-E; Bigerelle, M; Guillemot, G; Mansori, M El

2011-01-01

This article presents a multi-scale theory based on wavelet decomposition to characterize the evolution of roughness in relation with a finishing process or an observed surface property. To verify this approach in production conditions, analyses were developed for the finishing process of the hardened steel by abrasive belts. These conditions are described by seven parameters considered in the Tagushi experimental design. The main objective of this work is to identify the most relevant roughness parameter and characteristic length allowing to assess the influence of finishing process, and to test the relevance of the measurement scale. Results show that wavelet approach allows finding this scale.

Wavelet applications for modeling in the atmospheric sciences: Current status and potential extensions. Final report

International Nuclear Information System (INIS)

Envair, J.H.; Ekstrom, P.

1995-11-01

Wavelets are elementary mathematical functions used to construct, transform, and analyze higher functions and observational data. This report describes the results of an exploratory research effort to evaluate wavelet applications for numerically integrating differential equations associated with air pollution transport and conversion models. It is intended to provide a primer on wavelets, and specifically outlines the use of wavelets in a model that addresses derivative-evaluation and boundary-condition problems. Several factors complicate the use of wavelets for integrating differential equations. First, an enormous range of different wavelet types exists, making the choice of wavelet family for a given application challenging. Moreover, in contrast to the Fourier series, the functional derivatives necessary for numerical approximation are difficult to evaluate and consolidate in terms of wavelet expansions, introducing appreciable complexity into any attempt at wavelet-based integration. On the positive side, wavelet techniques do hold promise for effectively interfacing plume and other subgrid-scale phenomena in grid models. Moreover, workable techniques for derivative evaluation and simulation of boundary features appear feasible. Wavelet use may provide a viable, advantageous option for numerically integrating model equations describing fields on all scales of time and distance, especially where inhomogeneous fields exist, and provide a computationally efficient method of focusing on high-variability regions. The potential for wavelets to conduct integrations totally in transform space contrasts with Fourier-based approaches, which essentially preclude such treatments whenever nonlinear chemical processes occur in the modeled system

Clifford Continuous Wavelet Transforms in Ll0,2 and Ll0,3

International Nuclear Information System (INIS)

Bernstein, S.

2008-01-01

We consider Clifford-valued functions defined on R n . From the viewpoint of square integrable group representations a continuous wavelet transform is an irreducible continuous unitary representation of the affin group on the real line but also on R n . We will demonstrate that different Clifford continuous wavelet transforms can be obtained inside the calculus with similar properties than the real valued transform. Nevertheless, the Clifford wavelet transform is neither just a special vector transform nor just a wavelet transform applied to each component of the Clifford-valued function.

A new method for robust video watermarking resistant against key estimation attacks

Science.gov (United States)

Mitekin, Vitaly

2015-12-01

This paper presents a new method for high-capacity robust digital video watermarking and algorithms of embedding and extraction of watermark based on this method. Proposed method uses password-based two-dimensional pseudonoise arrays for watermark embedding, making brute-force attacks aimed at steganographic key retrieval mostly impractical. Proposed algorithm for 2-dimensional "noise-like" watermarking patterns generation also allows to significantly decrease watermark collision probability ( i.e. probability of correct watermark detection and extraction using incorrect steganographic key or password).. Experimental research provided in this work also shows that simple correlation-based watermark detection procedure can be used, providing watermark robustness against lossy compression and watermark estimation attacks. At the same time, without decreasing robustness of embedded watermark, average complexity of the brute-force key retrieval attack can be increased to 1014 watermark extraction attempts (compared to 104-106 for a known robust watermarking schemes). Experimental results also shows that for lowest embedding intensity watermark preserves it's robustness against lossy compression of host video and at the same time preserves higher video quality (PSNR up to 51dB) compared to known wavelet-based and DCT-based watermarking algorithms.

A comparison between wavelet based static and dynamic neural network approaches for runoff prediction

Science.gov (United States)

Shoaib, Muhammad; Shamseldin, Asaad Y.; Melville, Bruce W.; Khan, Mudasser Muneer

2016-04-01

In order to predict runoff accurately from a rainfall event, the multilayer perceptron type of neural network models are commonly used in hydrology. Furthermore, the wavelet coupled multilayer perceptron neural network (MLPNN) models has also been found superior relative to the simple neural network models which are not coupled with wavelet. However, the MLPNN models are considered as static and memory less networks and lack the ability to examine the temporal dimension of data. Recurrent neural network models, on the other hand, have the ability to learn from the preceding conditions of the system and hence considered as dynamic models. This study for the first time explores the potential of wavelet coupled time lagged recurrent neural network (TLRNN) models for runoff prediction using rainfall data. The Discrete Wavelet Transformation (DWT) is employed in this study to decompose the input rainfall data using six of the most commonly used wavelet functions. The performance of the simple and the wavelet coupled static MLPNN models is compared with their counterpart dynamic TLRNN models. The study found that the dynamic wavelet coupled TLRNN models can be considered as alternative to the static wavelet MLPNN models. The study also investigated the effect of memory depth on the performance of static and dynamic neural network models. The memory depth refers to how much past information (lagged data) is required as it is not known a priori. The db8 wavelet function is found to yield the best results with the static MLPNN models and with the TLRNN models having small memory depths. The performance of the wavelet coupled TLRNN models with large memory depths is found insensitive to the selection of the wavelet function as all wavelet functions have similar performance.

Evaluation of the Use of Second Generation Wavelets in the Coherent Vortex Simulation Approach

Science.gov (United States)

Goldstein, D. E.; Vasilyev, O. V.; Wray, A. A.; Rogallo, R. S.

2000-01-01

The objective of this study is to investigate the use of the second generation bi-orthogonal wavelet transform for the field decomposition in the Coherent Vortex Simulation of turbulent flows. The performances of the bi-orthogonal second generation wavelet transform and the orthogonal wavelet transform using Daubechies wavelets with the same number of vanishing moments are compared in a priori tests using a spectral direct numerical simulation (DNS) database of isotropic turbulence fields: 256(exp 3) and 512(exp 3) DNS of forced homogeneous turbulence (Re(sub lambda) = 168) and 256(exp 3) and 512(exp 3) DNS of decaying homogeneous turbulence (Re(sub lambda) = 55). It is found that bi-orthogonal second generation wavelets can be used for coherent vortex extraction. The results of a priori tests indicate that second generation wavelets have better compression and the residual field is closer to Gaussian. However, it was found that the use of second generation wavelets results in an integral length scale for the incoherent part that is larger than that derived from orthogonal wavelets. A way of dealing with this difficulty is suggested.

An adaptive wavelet-network model for forecasting daily total solar-radiation

International Nuclear Information System (INIS)

Mellit, A.; Benghanem, M.; Kalogirou, S.A.

2006-01-01

The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet-networks are feed-forward networks using wavelets as activation functions. Wavelet-networks have been used successfully in various engineering applications such as classification, identification and control problems. In this paper, the use of adaptive wavelet-network architecture in finding a suitable forecasting model for predicting the daily total solar-radiation is investigated. Total solar-radiation is considered as the most important parameter in the performance prediction of renewable energy systems, particularly in sizing photovoltaic (PV) power systems. For this purpose, daily total solar-radiation data have been recorded during the period extending from 1981 to 2001, by a meteorological station in Algeria. The wavelet-network model has been trained by using either the 19 years of data or one year of the data. In both cases the total solar radiation data corresponding to year 2001 was used for testing the model. The network was trained to accept and handle a number of unusual cases. Results indicate that the model predicts daily total solar-radiation values with a good accuracy of approximately 97% and the mean absolute percentage error is not more than 6%. In addition, the performance of the model was compared with different neural network structures and classical models. Training algorithms for wavelet-networks require smaller numbers of iterations when compared with other neural networks. The model can be used to fill missing data in weather databases. Additionally, the proposed model can be generalized and used in different locations and for other weather data, such as sunshine duration and ambient temperature. Finally, an application using the model for sizing a PV-power system is presented in order to confirm the validity of this model

Wavelet and Spectral Analysis of Some Selected Problems in Reactor Diagnostics

Energy Technology Data Exchange (ETDEWEB)

Sunde, Carl

2004-12-01

Both spectral and wavelet analysis were successfully used in various diagnostic problems involving non-stationary core processes in nuclear power reactors. Three different problems were treated: two-phase flow identification, detector tube impacting and core-barrel vibrations. The first two problems are of non-stationary nature, whereas the last one is not. In the first problem, neutron radiographic and visible light images of four different vertical two-phase flow regimes, bubbly, slug, chum and annular flow, were analysed and classified with a neuro-wavelet algorithm. The algorithm consists of a wavelet part, using the 2-D discrete wavelet transform and of an artificial neural network. It classifies the different flow regimes with up to 99% efficiency. Detector tubes in a Boiling Water Reactor may execute vibrations and may also impact on nearby fuel-assemblies. Signals from in-core neutron detectors in Ringhals-1 were analysed, for detection of impacting, with both a classical spectral method and wavelet-based methods. The wavelet methods include both the discrete and the continuous 1-D wavelet transform. It was found that there is agreement between the different methods as well as with visual inspections made during the outage at the plant. However, the wavelet technique has the advantage that it does not require expert judgement for the interpretation of the analysis. In the last part two analytical calculations of the neutron noise, induced by shell-mode core-barrel vibrations, were carried out. The results are in good agreement with calculations from a numerical simulator. An out-of-phase behaviour between in-core and ex-core positions was found, which is in agreement with earlier measurements from the Pressurised Water Reactor Ringhals-3. The results from these calculations are planned to be used when diagnosing the shell-mode core-barrel vibrations in an operating plant.

Wavelet and Spectral Analysis of Some Selected Problems in Reactor Diagnostics

International Nuclear Information System (INIS)

Sunde, Carl

2004-12-01

Both spectral and wavelet analysis were successfully used in various diagnostic problems involving non-stationary core processes in nuclear power reactors. Three different problems were treated: two-phase flow identification, detector tube impacting and core-barrel vibrations. The first two problems are of non-stationary nature, whereas the last one is not. In the first problem, neutron radiographic and visible light images of four different vertical two-phase flow regimes, bubbly, slug, chum and annular flow, were analysed and classified with a neuro-wavelet algorithm. The algorithm consists of a wavelet part, using the 2-D discrete wavelet transform and of an artificial neural network. It classifies the different flow regimes with up to 99% efficiency. Detector tubes in a Boiling Water Reactor may execute vibrations and may also impact on nearby fuel-assemblies. Signals from in-core neutron detectors in Ringhals-1 were analysed, for detection of impacting, with both a classical spectral method and wavelet-based methods. The wavelet methods include both the discrete and the continuous 1-D wavelet transform. It was found that there is agreement between the different methods as well as with visual inspections made during the outage at the plant. However, the wavelet technique has the advantage that it does not require expert judgement for the interpretation of the analysis. In the last part two analytical calculations of the neutron noise, induced by shell-mode core-barrel vibrations, were carried out. The results are in good agreement with calculations from a numerical simulator. An out-of-phase behaviour between in-core and ex-core positions was found, which is in agreement with earlier measurements from the Pressurised Water Reactor Ringhals-3. The results from these calculations are planned to be used when diagnosing the shell-mode core-barrel vibrations in an operating plant

ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit

OpenAIRE

Xiao, Zhihuai; He, Xinying; Fu, Xiangqian; Malik, O. P.

2015-01-01

Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO-) initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the fr...

Orthonormal Wavelet Bases for Quantum Molecular Dynamics

International Nuclear Information System (INIS)

Tymczak, C.; Wang, X.

1997-01-01

We report on the use of compactly supported, orthonormal wavelet bases for quantum molecular-dynamics (Car-Parrinello) algorithms. A wavelet selection scheme is developed and tested for prototypical problems, such as the three-dimensional harmonic oscillator, the hydrogen atom, and the local density approximation to atomic and molecular systems. Our method shows systematic convergence with increased grid size, along with improvement on compression rates, thereby yielding an optimal grid for self-consistent electronic structure calculations. copyright 1997 The American Physical Society

Wavelet and Blend maps for texture synthesis

OpenAIRE

Du Jin-Lian; Wang Song; Meng Xianhai

2011-01-01

blending is now a popular technology for large realtime texture synthesis .Nevertheless, creating blend map during rendering is time and computation consuming work. In this paper, we exploited a method to create a kind of blend tile which can be tile together seamlessly. Note that blend map is in fact a kind of image, which is Markov Random Field, contains multiresolution signals, while wavelet is a powerful way to process multiresolution signals, we use wavelet to process the traditional ble...

Digital Correlation based on Wavelet Transform for Image Detection

International Nuclear Information System (INIS)

Barba, L; Vargas, L; Torres, C; Mattos, L

2011-01-01

In this work is presented a method for the optimization of digital correlators to improve the characteristic detection on images using wavelet transform as well as subband filtering. It is proposed an approach of wavelet-based image contrast enhancement in order to increase the performance of digital correlators. The multiresolution representation is employed to improve the high frequency content of images taken into account the input contrast measured for the original image. The energy of correlation peaks and discrimination level of several objects are improved with this technique. To demonstrate the potentiality in extracting characteristics using the wavelet transform, small objects inside reference images are detected successfully.

The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance

Energy Technology Data Exchange (ETDEWEB)

Kingsbury, J Ng and N G [Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ (United Kingdom)

2004-02-06

This book provides an overview of the theory and practice of continuous and discrete wavelet transforms. Divided into seven chapters, the first three chapters of the book are introductory, describing the various forms of the wavelet transform and their computation, while the remaining chapters are devoted to applications in fluids, engineering, medicine and miscellaneous areas. Each chapter is well introduced, with suitable examples to demonstrate key concepts. Illustrations are included where appropriate, thus adding a visual dimension to the text. A noteworthy feature is the inclusion, at the end of each chapter, of a list of further resources from the academic literature which the interested reader can consult. The first chapter is purely an introduction to the text. The treatment of wavelet transforms begins in the second chapter, with the definition of what a wavelet is. The chapter continues by defining the continuous wavelet transform and its inverse and a description of how it may be used to interrogate signals. The continuous wavelet transform is then compared to the short-time Fourier transform. Energy and power spectra with respect to scale are also discussed and linked to their frequency counterparts. Towards the end of the chapter, the two-dimensional continuous wavelet transform is introduced. Examples of how the continuous wavelet transform is computed using the Mexican hat and Morlet wavelets are provided throughout. The third chapter introduces the discrete wavelet transform, with its distinction from the discretized continuous wavelet transform having been made clear at the end of the second chapter. In the first half of the chapter, the logarithmic discretization of the wavelet function is described, leading to a discussion of dyadic grid scaling, frames, orthogonal and orthonormal bases, scaling functions and multiresolution representation. The fast wavelet transform is introduced and its computation is illustrated with an example using the Haar

Wavelet-based ground vehicle recognition using acoustic signals

Science.gov (United States)

Choe, Howard C.; Karlsen, Robert E.; Gerhart, Grant R.; Meitzler, Thomas J.

1996-03-01

We present, in this paper, a wavelet-based acoustic signal analysis to remotely recognize military vehicles using their sound intercepted by acoustic sensors. Since expedited signal recognition is imperative in many military and industrial situations, we developed an algorithm that provides an automated, fast signal recognition once implemented in a real-time hardware system. This algorithm consists of wavelet preprocessing, feature extraction and compact signal representation, and a simple but effective statistical pattern matching. The current status of the algorithm does not require any training. The training is replaced by human selection of reference signals (e.g., squeak or engine exhaust sound) distinctive to each individual vehicle based on human perception. This allows a fast archiving of any new vehicle type in the database once the signal is collected. The wavelet preprocessing provides time-frequency multiresolution analysis using discrete wavelet transform (DWT). Within each resolution level, feature vectors are generated from statistical parameters and energy content of the wavelet coefficients. After applying our algorithm on the intercepted acoustic signals, the resultant feature vectors are compared with the reference vehicle feature vectors in the database using statistical pattern matching to determine the type of vehicle from where the signal originated. Certainly, statistical pattern matching can be replaced by an artificial neural network (ANN); however, the ANN would require training data sets and time to train the net. Unfortunately, this is not always possible for many real world situations, especially collecting data sets from unfriendly ground vehicles to train the ANN. Our methodology using wavelet preprocessing and statistical pattern matching provides robust acoustic signal recognition. We also present an example of vehicle recognition using acoustic signals collected from two different military ground vehicles. In this paper, we will

Applications of wavelet transforms for nuclear power plant signal analysis

International Nuclear Information System (INIS)

Seker, S.; Turkcan, E.; Upadhyaya, B.R.; Erbay, A.S.

1998-01-01

The safety of Nuclear Power Plants (NPPs) may be enhanced by the timely processing of information derived from multiple process signals from NPPs. The most widely used technique in signal analysis applications is the Fourier transform in the frequency domain to generate power spectral densities (PSD). However, the Fourier transform is global in nature and will obscure any non-stationary signal feature. Lately, a powerful technique called the Wavelet Transform, has been developed. This transform uses certain basis functions for representing the data in an effective manner, with capability for sub-band analysis and providing time-frequency localization as needed. This paper presents a brief overview of wavelets applied to the nuclear industry for signal processing and plant monitoring. The basic theory of Wavelets is also summarized. In order to illustrate the application of wavelet transforms data were acquired from the operating nuclear power plant Borssele in the Netherlands. The experimental data consist of various signals in the power plant and are selected from a stationary power operation. Their frequency characteristics and the mutual relations were investigated using MATLAB signal processing and wavelet toolbox for computing their PSDs and coherence functions by multi-resolution analysis. The results indicate that the sub-band PSD matches with the original signal PSD and enhances the estimation of coherence functions. The Wavelet analysis demonstrates the feasibility of application to stationary signals to provide better estimates in the frequency band of interest as compared to the classical FFT approach. (author)

Applications of wavelets in morphometric analysis of medical images

Science.gov (United States)

Davatzikos, Christos; Tao, Xiaodong; Shen, Dinggang

2003-11-01

Morphometric analysis of medical images is playing an increasingly important role in understanding brain structure and function, as well as in understanding the way in which these change during development, aging and pathology. This paper presents three wavelet-based methods with related applications in morphometric analysis of magnetic resonance (MR) brain images. The first method handles cases where very limited datasets are available for the training of statistical shape models in the deformable segmentation. The method is capable of capturing a larger range of shape variability than the standard active shape models (ASMs) can, by using the elegant spatial-frequency decomposition of the shape contours provided by wavelet transforms. The second method addresses the difficulty of finding correspondences in anatomical images, which is a key step in shape analysis and deformable registration. The detection of anatomical correspondences is completed by using wavelet-based attribute vectors as morphological signatures of voxels. The third method uses wavelets to characterize the morphological measurements obtained from all voxels in a brain image, and the entire set of wavelet coefficients is further used to build a brain classifier. Since the classification scheme operates in a very-high-dimensional space, it can determine subtle population differences with complex spatial patterns. Experimental results are provided to demonstrate the performance of the proposed methods.

Image encryption using the fractional wavelet transform

International Nuclear Information System (INIS)

Vilardy, Juan M; Useche, J; Torres, C O; Mattos, L

2011-01-01

In this paper a technique for the coding of digital images is developed using Fractional Wavelet Transform (FWT) and random phase masks (RPMs). The digital image to encrypt is transformed with the FWT, after the coefficients resulting from the FWT (Approximation, Details: Horizontal, vertical and diagonal) are multiplied each one by different RPMs (statistically independent) and these latest results is applied an Inverse Wavelet Transform (IWT), obtaining the encrypted digital image. The decryption technique is the same encryption technique in reverse sense. This technique provides immediate advantages security compared to conventional techniques, in this technique the mother wavelet family and fractional orders associated with the FWT are additional keys that make access difficult to information to an unauthorized person (besides the RPMs used), thereby the level of encryption security is extraordinarily increased. In this work the mathematical support for the use of the FWT in the computational algorithm for the encryption is also developed.

ECG denoising with adaptive bionic wavelet transform.

Science.gov (United States)

Sayadi, Omid; Shamsollahi, Mohammad Bagher

2006-01-01

In this paper a new ECG denoising scheme is proposed using a novel adaptive wavelet transform, named bionic wavelet transform (BWT), which had been first developed based on a model of the active auditory system. There has been some outstanding features with the BWT such as nonlinearity, high sensitivity and frequency selectivity, concentrated energy distribution and its ability to reconstruct signal via inverse transform but the most distinguishing characteristic of BWT is that its resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT parameters parallel to modifying a new threshold value, one can handle ECG denoising with results comparing to those of wavelet transform (WT). Preliminary tests of BWT application to ECG denoising were constructed on the signals of MIT-BIH database which showed high performance of noise reduction.

Wavelet Types Comparison for Extracting Iris Feature Based on Energy Compaction

Science.gov (United States)

Rizal Isnanto, R.

2015-06-01

Human iris has a very unique pattern which is possible to be used as a biometric recognition. To identify texture in an image, texture analysis method can be used. One of method is wavelet that extract the image feature based on energy. Wavelet transforms used are Haar, Daubechies, Coiflets, Symlets, and Biorthogonal. In the research, iris recognition based on five mentioned wavelets was done and then comparison analysis was conducted for which some conclusions taken. Some steps have to be done in the research. First, the iris image is segmented from eye image then enhanced with histogram equalization. The features obtained is energy value. The next step is recognition using normalized Euclidean distance. Comparison analysis is done based on recognition rate percentage with two samples stored in database for reference images. After finding the recognition rate, some tests are conducted using Energy Compaction for all five types of wavelets above. As the result, the highest recognition rate is achieved using Haar, whereas for coefficients cutting for C(i) < 0.1, Haar wavelet has a highest percentage, therefore the retention rate or significan coefficient retained for Haaris lower than other wavelet types (db5, coif3, sym4, and bior2.4)

Sparse data structure design for wavelet-based methods

Directory of Open Access Journals (Sweden)

Latu Guillaume

2011-12-01

Full Text Available This course gives an introduction to the design of efficient datatypes for adaptive wavelet-based applications. It presents some code fragments and benchmark technics useful to learn about the design of sparse data structures and adaptive algorithms. Material and practical examples are given, and they provide good introduction for anyone involved in the development of adaptive applications. An answer will be given to the question: how to implement and efficiently use the discrete wavelet transform in computer applications? A focus will be made on time-evolution problems, and use of wavelet-based scheme for adaptively solving partial differential equations (PDE. One crucial issue is that the benefits of the adaptive method in term of algorithmic cost reduction can not be wasted by overheads associated to sparse data management.

Properties of wavelet discretization of Black-Scholes equation

Science.gov (United States)

Finěk, Václav

2017-07-01

Using wavelet methods, the continuous problem is transformed into a well-conditioned discrete problem. And once a non-symmetric problem is given, squaring yields a symmetric positive definite formulation. However squaring usually makes the condition number of discrete problems substantially worse. This note is concerned with a wavelet based numerical solution of the Black-Scholes equation for pricing European options. We show here that in wavelet coordinates a symmetric part of the discretized equation dominates over an unsymmetric part in the standard economic environment with low interest rates. It provides some justification for using a fractional step method with implicit treatment of the symmetric part of the weak form of the Black-Scholes operator and with explicit treatment of its unsymmetric part. Then a well-conditioned discrete problem is obtained.

Comparative study of wavelets of the first and second generation

International Nuclear Information System (INIS)

Ososkov, G.A.; Shitov, A.B.; Stadnik, A.V.

2001-01-01

In order to compare efficiency a comprehensive set of benchmarking tests is developed, which is used to compare abilities of continuous wavelet transform of the vanishing momenta type as well as the second generation wavelets constructed on the basis of the lifting scheme. It is based on processing of various types of pure and contaminated harmonic signals, delta-function, study of the signal phase dependence and the gain-frequency characteristics. The results of a comparative multiscale analysis allow one to reveal advantages and flaws of the considered types of wavelets

Multidimensional filter banks and wavelets research developments and applications

CERN Document Server

Levy, Bernard

1997-01-01

Multidimensional Filter Banks and Wavelets: Reserach Developments and Applications brings together in one place important contributions and up-to-date research results in this important area. Multidimensional Filter Banks and Wavelets: Research Developments and Applications serves as an excellent reference, providing insight into some of the most important research issues in the field.

Adaptive wavelet collocation methods for initial value boundary problems of nonlinear PDE's

Science.gov (United States)

Cai, Wei; Wang, Jian-Zhong

1993-01-01

We have designed a cubic spline wavelet decomposition for the Sobolev space H(sup 2)(sub 0)(I) where I is a bounded interval. Based on a special 'point-wise orthogonality' of the wavelet basis functions, a fast Discrete Wavelet Transform (DWT) is constructed. This DWT transform will map discrete samples of a function to its wavelet expansion coefficients in O(N log N) operations. Using this transform, we propose a collocation method for the initial value boundary problem of nonlinear PDE's. Then, we test the efficiency of the DWT transform and apply the collocation method to solve linear and nonlinear PDE's.

The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance

International Nuclear Information System (INIS)

Kingsbury, J Ng and N G

2004-01-01

This book provides an overview of the theory and practice of continuous and discrete wavelet transforms. Divided into seven chapters, the first three chapters of the book are introductory, describing the various forms of the wavelet transform and their computation, while the remaining chapters are devoted to applications in fluids, engineering, medicine and miscellaneous areas. Each chapter is well introduced, with suitable examples to demonstrate key concepts. Illustrations are included where appropriate, thus adding a visual dimension to the text. A noteworthy feature is the inclusion, at the end of each chapter, of a list of further resources from the academic literature which the interested reader can consult. The first chapter is purely an introduction to the text. The treatment of wavelet transforms begins in the second chapter, with the definition of what a wavelet is. The chapter continues by defining the continuous wavelet transform and its inverse and a description of how it may be used to interrogate signals. The continuous wavelet transform is then compared to the short-time Fourier transform. Energy and power spectra with respect to scale are also discussed and linked to their frequency counterparts. Towards the end of the chapter, the two-dimensional continuous wavelet transform is introduced. Examples of how the continuous wavelet transform is computed using the Mexican hat and Morlet wavelets are provided throughout. The third chapter introduces the discrete wavelet transform, with its distinction from the discretized continuous wavelet transform having been made clear at the end of the second chapter. In the first half of the chapter, the logarithmic discretization of the wavelet function is described, leading to a discussion of dyadic grid scaling, frames, orthogonal and orthonormal bases, scaling functions and multiresolution representation. The fast wavelet transform is introduced and its computation is illustrated with an example using the Haar

Wavelets in self-consistent electronic structure calculations

International Nuclear Information System (INIS)

Wei, S.; Chou, M.Y.

1996-01-01

We report the first implementation of orthonormal wavelet bases in self-consistent electronic structure calculations within the local-density approximation. These local bases of different scales efficiently describe localized orbitals of interest. As an example, we studied two molecules, H 2 and O 2 , using pseudopotentials and supercells. Considerably fewer bases are needed compared with conventional plane-wave approaches, yet calculated binding properties are similar. Our implementation employs fast wavelet and Fourier transforms, avoiding evaluating any three-dimensional integral numerically. copyright 1996 The American Physical Society

Multiresolution signal decomposition transforms, subbands, and wavelets

CERN Document Server

Akansu, Ali N; Haddad, Paul R

2001-01-01

The uniqueness of this book is that it covers such important aspects of modern signal processing as block transforms from subband filter banks and wavelet transforms from a common unifying standpoint, thus demonstrating the commonality among these decomposition techniques. In addition, it covers such ""hot"" areas as signal compression and coding, including particular decomposition techniques and tables listing coefficients of subband and wavelet filters and other important properties.The field of this book (Electrical Engineering/Computer Science) is currently booming, which is, of course

Numerical simulation for fractional order stationary neutron transport equation using Haar wavelet collocation method

Energy Technology Data Exchange (ETDEWEB)

Saha Ray, S., E-mail: santanusaharay@yahoo.com; Patra, A.

2014-10-15

Highlights: • A stationary transport equation has been solved using the technique of Haar wavelet collocation method. • This paper intends to provide the great utility of Haar wavelets to nuclear science problem. • In the present paper, two-dimensional Haar wavelets are applied. • The proposed method is mathematically very simple, easy and fast. - Abstract: In this paper the numerical solution for the fractional order stationary neutron transport equation is presented using Haar wavelet Collocation Method (HWCM). Haar wavelet collocation method is efficient and powerful in solving wide class of linear and nonlinear differential equations. This paper intends to provide an application of Haar wavelets to nuclear science problems. This paper describes the application of Haar wavelets for the numerical solution of fractional order stationary neutron transport equation in homogeneous medium with isotropic scattering. The proposed method is mathematically very simple, easy and fast. To demonstrate about the efficiency and applicability of the method, two test problems are discussed.

Value-at-risk estimation with wavelet-based extreme value theory: Evidence from emerging markets

Science.gov (United States)

Cifter, Atilla

2011-06-01

This paper introduces wavelet-based extreme value theory (EVT) for univariate value-at-risk estimation. Wavelets and EVT are combined for volatility forecasting to estimate a hybrid model. In the first stage, wavelets are used as a threshold in generalized Pareto distribution, and in the second stage, EVT is applied with a wavelet-based threshold. This new model is applied to two major emerging stock markets: the Istanbul Stock Exchange (ISE) and the Budapest Stock Exchange (BUX). The relative performance of wavelet-based EVT is benchmarked against the Riskmetrics-EWMA, ARMA-GARCH, generalized Pareto distribution, and conditional generalized Pareto distribution models. The empirical results show that the wavelet-based extreme value theory increases predictive performance of financial forecasting according to number of violations and tail-loss tests. The superior forecasting performance of the wavelet-based EVT model is also consistent with Basel II requirements, and this new model can be used by financial institutions as well.

Image Vector Quantization codec indexes filtering

Directory of Open Access Journals (Sweden)

Lakhdar Moulay Abdelmounaim

2012-01-01

Full Text Available Vector Quantisation (VQ is an efficient coding algorithm that has been widely used in the field of video and image coding, due to its fast decoding efficiency. However, the indexes of VQ are sometimes lost because of signal interference during the transmission. In this paper, we propose an efficient estimation method to conceal and recover the lost indexes on the decoder side, to avoid re-transmitting the whole image again. If the image or video has the limitation of a period of validity, re-transmitting the data wastes the resources of time and network bandwidth. Therefore, using the originally received correct data to estimate and recover the lost data is efficient in time-constrained situations, such as network conferencing or mobile transmissions. In nature images, the pixels are correlated with their neighbours and VQ partitions the image into sub-blocks and quantises them to the indexes that are transmitted; the correlation between adjacent indexes is very strong. There are two parts of the proposed method. The first is pre-processing and the second is an estimation process. In pre-processing, we modify the order of codevectors in the VQ codebook to increase the correlation among the neighbouring vectors. We then use a special filtering method in the estimation process. Using conventional VQ to compress the Lena image and transmit it without any loss of index can achieve a PSNR of 30.429 dB on the decoder. The simulation results demonstrate that our method can estimate the indexes to achieve PSNR values of 29.084 and 28.327 dB when the loss rate is 0.5% and 1%, respectively.

Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach

Science.gov (United States)

Aloui, Chaker; Jammazi, Rania

2015-10-01

In this article, we propose a wavelet-based approach to accommodate the stylized facts and complex structure of financial data, caused by frequent and abrupt changes of markets and noises. Specifically, we show how the combination of both continuous and discrete wavelet transforms with traditional financial models helps improve portfolio's market risk assessment. In the empirical stage, three wavelet-based models (wavelet-EGARCH with dynamic conditional correlations, wavelet-copula, and wavelet-extreme value) are considered and applied to crude oil price and US dollar exchange rate data. Our findings show that the wavelet-based approach provides an effective and powerful tool for detecting extreme moments and improving the accuracy of VaR and Expected Shortfall estimates of oil-exchange rate portfolios after noise is removed from the original data.

Analysis of the tennis racket vibrations during forehand drives: Selection of the mother wavelet.

Science.gov (United States)

Blache, Y; Hautier, C; Lefebvre, F; Djordjevic, A; Creveaux, T; Rogowski, I

2017-08-16

The time-frequency analysis of the tennis racket and hand vibrations is of great interest for discomfort and pathology prevention. This study aimed to (i) to assess the stationarity of the vibratory signal of the racket and hand and (ii) to identify the best mother wavelet to perform future time-frequency analysis, (iii) to determine if the stroke spin, racket characteristics and impact zone can influence the selection of the best mother wavelet. A total of 2364 topspin and flat forehand drives were performed by fourteen male competitive tennis players with six different rackets. One tri-axial and one mono-axial accelerometer were taped on the racket throat and dominant hand respectively. The signal stationarity was tested through the wavelet spectrum test. Eighty-nine mother wavelet were tested to select the best mother wavelet based on continuous and discrete transforms. On average only 25±17%, 2±5%, 5±7% and 27±27% of the signal tested respected the hypothesis of stationarity for the three axes of the racket and the hand respectively. Regarding the two methods for the detection of the best mother wavelet, the Daubechy 45 wavelet presented the highest average ranking. No effect of the stroke spin, racket characteristics and impact zone was observed for the selection of the best mother wavelet. It was concluded that alternative approach to Fast Fourier Transform should be used to interpret tennis vibration signals. In the case where wavelet transform is chosen, the Daubechy 45 mother wavelet appeared to be the most suitable. Copyright © 2017 Elsevier Ltd. All rights reserved.

Standard filter approximations for low power Continuous Wavelet Transforms.

Science.gov (United States)

Casson, Alexander J; Rodriguez-Villegas, Esther

2010-01-01

Analogue domain implementations of the Continuous Wavelet Transform (CWT) have proved popular in recent years as they can be implemented at very low power consumption levels. This is essential for use in wearable, long term physiological monitoring systems. Present analogue CWT implementations rely on taking mathematical a approximation of the wanted mother wavelet function to give a filter transfer function that is suitable for circuit implementation. This paper investigates the use of standard filter approximations (Butterworth, Chebyshev, Bessel) as an alternative wavelet approximation technique. This extends the number of approximation techniques available for generating analogue CWT filters. An example ECG analysis shows that signal information can be successfully extracted using these CWT approximations.

Wavelet Based Hilbert Transform with Digital Design and Application to QCM-SS Watermarking

Directory of Open Access Journals (Sweden)

S. P. Maity

2008-04-01

Full Text Available In recent time, wavelet transforms are used extensively for efficient storage, transmission and representation of multimedia signals. Hilbert transform pairs of wavelets is the basic unit of many wavelet theories such as complex filter banks, complex wavelet and phaselet etc. Moreover, Hilbert transform finds various applications in communications and signal processing such as generation of single sideband (SSB modulation, quadrature carrier multiplexing (QCM and bandpass representation of a signal. Thus wavelet based discrete Hilbert transform design draws much attention of researchers for couple of years. This paper proposes an (i algorithm for generation of low computation cost Hilbert transform pairs of symmetric filter coefficients using biorthogonal wavelets, (ii approximation to its rational coefficients form for its efficient hardware realization and without much loss in signal representation, and finally (iii development of QCM-SS (spread spectrum image watermarking scheme for doubling the payload capacity. Simulation results show novelty of the proposed Hilbert transform design and its application to watermarking compared to existing algorithms.

Wavelet based analysis of multi-electrode EEG-signals in epilepsy

Science.gov (United States)

Hein, Daniel A.; Tetzlaff, Ronald

2005-06-01

For many epilepsy patients seizures cannot sufficiently be controlled by an antiepileptic pharmacatherapy. Furthermore, only in small number of cases a surgical treatment may be possible. The aim of this work is to contribute to the realization of an implantable seizure warning device. By using recordings of electroenzephalographical(EEG) signals obtained from the department of epileptology of the University of Bonn we studied a recently proposed algorithm for the detection of parameter changes in nonlinear systems. Firstly, after calculating the crosscorrelation function between the signals of two electrodes near the epileptic focus, a wavelet-analysis follows using a sliding window with the so called Mexican-Hat wavelet. Then the Shannon-Entropy of the wavelet-transformed data has been determined providing the information content on a time scale in subject to the dilation of the wavelet-transformation. It shows distinct changes at the seizure onset for all dilations and for all patients.

Complex Wavelet transform for MRI

International Nuclear Information System (INIS)

Junor, P.; Janney, P.

2004-01-01

Full text: There is a perpetual compromise encountered in magnetic resonance (MRl) image reconstruction, between the traditional elements of image quality (noise, spatial resolution and contrast). Additional factors exacerbating this trade-off include various artifacts, computational (and hence time-dependent) overhead, and financial expense. This paper outlines a new approach to the problem of minimizing MRI image acquisition and reconstruction time without compromising resolution and noise reduction. The standard approaches for reconstructing magnetic resonance (MRI) images from raw data (which rely on relatively conventional signal processing) have matured but there are a number of challenges which limit their use. A major one is the 'intrinsic' signal-to-noise ratio (SNR) of the reconstructed image that depends on the strength of the main field. A typical clinical MRI almost invariably uses a super-cooled magnet in order to achieve a high field strength. The ongoing running cost of these super-cooled magnets prompts consideration of alternative magnet systems for use in MRIs for developing countries and in some remote regional installations. The decrease in image quality from using lower field strength magnets can be addressed by improvements in signal processing strategies. Conversely, improved signal processing will obviously benefit the current conventional field strength MRI machines. Moreover, the 'waiting time' experienced in many MR sequences (due to the relaxation time delays) can be exploited by more rigorous processing of the MR signals. Acquisition often needs to be repeated so that coherent averaging may partially redress the shortfall in SNR, at the expense of further delay. Wavelet transforms have been used in MRI as an alternative for encoding and denoising for over a decade. These have not supplanted the traditional Fourier transform methods that have long been the mainstay of MRI reconstruction, but have some inflexibility. The dual

A new DWT/MC/DPCM video compression framework based on EBCOT

Science.gov (United States)

Mei, L. M.; Wu, H. R.; Tan, D. M.

2005-07-01

A novel Discrete Wavelet Transform (DWT)/Motion Compensation (MC)/Differential Pulse Code Modulation (DPCM) video compression framework is proposed in this paper. Although the Discrete Cosine Transform (DCT)/MC/DPCM is the mainstream framework for video coders in industry and international standards, the idea of DWT/MC/DPCM has existed for more than one decade in the literature and the investigation is still undergoing. The contribution of this work is twofold. Firstly, the Embedded Block Coding with Optimal Truncation (EBCOT) is used here as the compression engine for both intra- and inter-frame coding, which provides good compression ratio and embedded rate-distortion (R-D) optimization mechanism. This is an extension of the EBCOT application from still images to videos. Secondly, this framework offers a good interface for the Perceptual Distortion Measure (PDM) based on the Human Visual System (HVS) where the Mean Squared Error (MSE) can be easily replaced with the PDM in the R-D optimization. Some of the preliminary results are reported here. They are also compared with benchmarks such as MPEG-2 and MPEG-4 version 2. The results demonstrate that under specified condition the proposed coder outperforms the benchmarks in terms of rate vs. distortion.

Wavelet analysis of epileptic spikes

Science.gov (United States)

Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-05-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

Wavelet analysis of epileptic spikes

CERN Document Server

Latka, M; Kozik, A; West, B J; Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-01-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

A New Wavelet Threshold Function and Denoising Application

Directory of Open Access Journals (Sweden)

Lu Jing-yi

2016-01-01

Full Text Available In order to improve the effects of denoising, this paper introduces the basic principles of wavelet threshold denoising and traditional structures threshold functions. Meanwhile, it proposes wavelet threshold function and fixed threshold formula which are both improved here. First, this paper studies the problems existing in the traditional wavelet threshold functions and introduces the adjustment factors to construct the new threshold function basis on soft threshold function. Then, it studies the fixed threshold and introduces the logarithmic function of layer number of wavelet decomposition to design the new fixed threshold formula. Finally, this paper uses hard threshold, soft threshold, Garrote threshold, and improved threshold function to denoise different signals. And the paper also calculates signal-to-noise (SNR and mean square errors (MSE of the hard threshold functions, soft thresholding functions, Garrote threshold functions, and the improved threshold function after denoising. Theoretical analysis and experimental results showed that the proposed approach could improve soft threshold functions with constant deviation and hard threshold with discontinuous function problems. The proposed approach could improve the different decomposition scales that adopt the same threshold value to deal with the noise problems, also effectively filter the noise in the signals, and improve the SNR and reduce the MSE of output signals.

Wavelet Filter Banks for Super-Resolution SAR Imaging

Science.gov (United States)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Wavelet methods in mathematical analysis and engineering

CERN Document Server

Damlamian, Alain

2010-01-01

This book gives a comprehensive overview of both the fundamentals of wavelet analysis and related tools, and of the most active recent developments towards applications. It offers a stateoftheart in several active areas of research where wavelet ideas, or more generally multiresolution ideas have proved particularly effective. The main applications covered are in the numerical analysis of PDEs, and signal and image processing. Recently introduced techniques such as Empirical Mode Decomposition (EMD) and new trends in the recovery of missing data, such as compressed sensing, are also presented.

Solution of neutron transport equation using Daubechies' wavelet expansion in the angular discretization

International Nuclear Information System (INIS)

Cao Liangzhi; Wu Hongchun; Zheng Youqi

2008-01-01

Daubechies' wavelet expansion is introduced to discretize the angular variables of the neutron transport equation when the neutron angular flux varies very acutely with the angular directions. An improvement is made by coupling one-dimensional wavelet expansion and discrete ordinate method to make two-dimensional angular discretization efficient and stable. The angular domain is divided into several subdomains for treating the vacuum boundary condition exactly in the unstructured geometry. A set of wavelet equations coupled with each other is obtained in each subdomain. An iterative method is utilized to decouple the wavelet moments. The numerical results of several benchmark problems demonstrate that the wavelet expansion method can provide more accurate results by lower-order expansion than other angular discretization methods

Wavelet-transform-based time–frequency domain reflectometry for reduction of blind spot

International Nuclear Information System (INIS)

Lee, Sin Ho; Park, Jin Bae; Choi, Yoon Ho

2012-01-01

In this paper, wavelet-transform-based time–frequency domain reflectometry (WTFDR) is proposed to reduce the blind spot in reflectometry. TFDR has a blind spot problem when the time delay between the reference signal and the reflected signal is short enough compared with the time duration of the reference signal. To solve the blind spot problem, the wavelet transform (WT) is used because the WT has linearity. Using the characteristics of the WT, the overlapped reference signal at the measured signal can be separated and the blind spot is reduced by obtaining the difference of the wavelet coefficients for the reference and reflected signals. In the proposed method, the complex wavelet is utilized as a mother wavelet because the reference signal in WTFDR has a complex form. Finally, the computer simulations and the real experiments are carried out to confirm the effectiveness and accuracy of the proposed method. (paper)

Identification Method of Mud Shale Fractures Base on Wavelet Transform

Science.gov (United States)

Xia, Weixu; Lai, Fuqiang; Luo, Han

2018-01-01

In recent years, inspired by seismic analysis technology, a new method for analysing mud shale fractures oil and gas reservoirs by logging properties has emerged. By extracting the high frequency attribute of the wavelet transform in the logging attribute, the formation information hidden in the logging signal is extracted, identified the fractures that are not recognized by conventional logging and in the identified fracture segment to show the “cycle jump”, “high value”, “spike” and other response effect is more obvious. Finally formed a complete wavelet denoising method and wavelet high frequency identification fracture method.

Fast, large-scale hologram calculation in wavelet domain

Science.gov (United States)

Shimobaba, Tomoyoshi; Matsushima, Kyoji; Takahashi, Takayuki; Nagahama, Yuki; Hasegawa, Satoki; Sano, Marie; Hirayama, Ryuji; Kakue, Takashi; Ito, Tomoyoshi

2018-04-01

We propose a large-scale hologram calculation using WAvelet ShrinkAge-Based superpositIon (WASABI), a wavelet transform-based algorithm. An image-type hologram calculated using the WASABI method is printed on a glass substrate with the resolution of 65 , 536 × 65 , 536 pixels and a pixel pitch of 1 μm. The hologram calculation time amounts to approximately 354 s on a commercial CPU, which is approximately 30 times faster than conventional methods.

Hydrological model performance and parameter estimation in the wavelet-domain

Directory of Open Access Journals (Sweden)

B. Schaefli

2009-10-01

Full Text Available This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights the frequencies that are not well reproduced by the model, which gives specific indications about how to improve the model structure.

Exploring an optimal wavelet-based filter for cryo-ET imaging.

Science.gov (United States)

Huang, Xinrui; Li, Sha; Gao, Song

2018-02-07

Cryo-electron tomography (cryo-ET) is one of the most advanced technologies for the in situ visualization of molecular machines by producing three-dimensional (3D) biological structures. However, cryo-ET imaging has two serious disadvantages-low dose and low image contrast-which result in high-resolution information being obscured by noise and image quality being degraded, and this causes errors in biological interpretation. The purpose of this research is to explore an optimal wavelet denoising technique to reduce noise in cryo-ET images. We perform tests using simulation data and design a filter using the optimum selected wavelet parameters (three-level decomposition, level-1 zeroed out, subband-dependent threshold, a soft-thresholding and spline-based discrete dyadic wavelet transform (DDWT)), which we call a modified wavelet shrinkage filter; this filter is suitable for noisy cryo-ET data. When testing using real cryo-ET experiment data, higher quality images and more accurate measures of a biological structure can be obtained with the modified wavelet shrinkage filter processing compared with conventional processing. Because the proposed method provides an inherent advantage when dealing with cryo-ET images, it can therefore extend the current state-of-the-art technology in assisting all aspects of cryo-ET studies: visualization, reconstruction, structural analysis, and interpretation.

Steerable dyadic wavelet transform and interval wavelets for enhancement of digital mammography

Science.gov (United States)

Laine, Andrew F.; Koren, Iztok; Yang, Wuhai; Taylor, Fred J.

1995-04-01

This paper describes two approaches for accomplishing interactive feature analysis by overcomplete multiresolution representations. We show quantitatively that transform coefficients, modified by an adaptive non-linear operator, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. Our results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. We design a filter bank representing a steerable dyadic wavelet transform that can be used for multiresolution analysis along arbitrary orientations. Digital mammograms are enhanced by orientation analysis performed by a steerable dyadic wavelet transform. Arbitrary regions of interest (ROI) are enhanced by Deslauriers-Dubuc interpolation representations on an interval. We demonstrate that our methods can provide radiologists with an interactive capability to support localized processing of selected (suspicion) areas (lesions). Features extracted from multiscale representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology can improve changes of early detection while requiring less time to evaluate mammograms for most patients.

Constructing a two bands optical code-division multiple-access network of bipolar optical access codecs using Walsh-coded liquid crystal modulators

Science.gov (United States)

Yen, Chih-Ta; Huang, Jen-Fa; Chih, Ping-En

2014-08-01

We propose and experimentally demonstrated the two bands optical code-division multiple-access (OCDMA) network over bipolar Walsh-coded liquid-crystal modulators (LCMs) and driven by green light and red light lasers. Achieving system performance depends on the construction of a decoder that implements a true bipolar correlation using only unipolar signals and intensity detection for each band. We took advantage of the phase delay characteristics of LCMs to construct a prototype optical coder/decoder (codec). Matched and unmatched Walsh signature codes were evaluated to detect correlations among multiuser data in the access network. By using LCMs, a red and green laser light source was spectrally encoded and the summed light dots were complementary decoded. Favorable contrast on auto- and cross-correlations indicates that binary information symbols can be properly recovered using a balanced photodetector.

Comparative study on γ energy spectrum denoise by fourier and wavelet transforms

International Nuclear Information System (INIS)

Shi Dongsheng; Di Yuming; Zhou Chunlin

2007-01-01

This paper introduces the basic principle of wavelet and Fourier transforms, applies wavelet transform method to denoise γ energy spectrum of 60 Co and compares it with Fourier transform method. The result of simulation with MATLAB software tool showed that as compared with traditional Fourier transform, wavelet transform has comparatively higher accuracy for γ energy spectrum denoising and is more feasible to γ energy spectrum denoising. (authors)

A STUDY OF WAVELET ENTROPY MEASURE DEFINITION AND ITS APPLICATION FOR FAULT FEATURE PICK-UP AND CLASSIFICATION

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Shannon entropy in time domain is a measure of signal or system uncertainty. When based on spectrum entropy, Shannon entropy can be taken as a measure of signal or system complexity.Therefore, wavelet analysis based on wavelet entropy measure can signify the complexity of non-steady signal or system in both time and frequency domain. In this paper, in order to meet the requirements of post-analysis on abundant wavelet transform result data and the need of information mergence, the basic definition of wavelet entropy measure is proposed, corresponding algorithms of several wavelet entropies, such as wavelet average entropy, wavelet time-frequency entropy, wavelet distance entropy,etc. are put forward, and the physical meanings of these entropies are analyzed as well. The application principle of wavelet entropy measure in ElectroEncephaloGraphy (EEG) signal analysis, mechanical fault diagnosis, fault detection and classification in power system are analyzed. Finally, take the transmission line fault detection in power system for example, simulations in two different systems, a 10kV automatic blocking and continuous power transmission line and a 500kV Extra High Voltage (EHV) transmission line, are carried out, and the two methods, wavelet entropy and wavelet modulus maxima, are compared, the results show feasibility and application prospect of the six wavelet entropies.

A Comparative Analysis for Selection of Appropriate Mother Wavelet for Detection of Stationary Disturbances

Science.gov (United States)

Kamble, Saurabh Prakash; Thawkar, Shashank; Gaikwad, Vinayak G.; Kothari, D. P.

2017-12-01

Detection of disturbances is the first step of mitigation. Power electronics plays a crucial role in modern power system which makes system operation efficient but it also bring stationary disturbances in the power system and added impurities to the supply. It happens because of the non-linear loads used in modern day power system which inject disturbances like harmonic disturbances, flickers, sag etc. in power grid. These impurities can damage equipments so it is necessary to mitigate these impurities present in the supply very quickly. So, digital signal processing techniques are incorporated for detection purpose. Signal processing techniques like fast Fourier transform, short-time Fourier transform, Wavelet transform etc. are widely used for the detection of disturbances. Among all, wavelet transform is widely used because of its better detection capabilities. But, which mother wavelet has to use for detection is still a mystery. Depending upon the periodicity, the disturbances are classified as stationary and non-stationary disturbances. This paper presents the importance of selection of mother wavelet for analyzing stationary disturbances using discrete wavelet transform. Signals with stationary disturbances of various frequencies are generated using MATLAB. The analysis of these signals is done using various mother wavelets like Daubechies and bi-orthogonal wavelets and the measured root mean square value of stationary disturbance is obtained. The measured value obtained by discrete wavelet transform is compared with the exact RMS value of the frequency component and the percentage differences are presented which helps to select optimum mother wavelet.

Comparisons between two wavelet functions in extracting coherent structures from solar wind time series

International Nuclear Information System (INIS)

Bolzani, M.J.A.; Guarnieri, F.L.; Vieira, Paulo Cesar

2009-01-01

Nowadays, wavelet analysis of turbulent flows have become increasingly popular. However, the study of geometric characteristics from wavelet functions is still poorly explored. In this work we compare the performance of two wavelet functions in extracting the coherent structures from solar wind velocity time series. The data series are from years 1996 to 2002 (except 1998 and 1999). The wavelet algorithm decomposes the annual time-series in two components: the coherent part and non-coherent one, using the daubechies-4 and haar wavelet function. The threshold assumed is based on a percentage of maximum variance found in each dyadic scale. After the extracting procedure, we applied the power spectral density on the original time series and coherent time series to obtain spectral indices. The results from spectral indices show higher values for the coherent part obtained by daubechies-4 than those obtained by the haar wavelet function. Using the kurtosis statistical parameter, on coherent and non-coherent time series, it was possible to conjecture that the differences found between two wavelet functions may be associated with their geometric forms. (author)

Method and system for progressive mesh storage and reconstruction using wavelet-encoded height fields

Science.gov (United States)

Baxes, Gregory A. (Inventor); Linger, Timothy C. (Inventor)

2011-01-01

Systems and methods are provided for progressive mesh storage and reconstruction using wavelet-encoded height fields. A method for progressive mesh storage includes reading raster height field data, and processing the raster height field data with a discrete wavelet transform to generate wavelet-encoded height fields. In another embodiment, a method for progressive mesh storage includes reading texture map data, and processing the texture map data with a discrete wavelet transform to generate wavelet-encoded texture map fields. A method for reconstructing a progressive mesh from wavelet-encoded height field data includes determining terrain blocks, and a level of detail required for each terrain block, based upon a viewpoint. Triangle strip constructs are generated from vertices of the terrain blocks, and an image is rendered utilizing the triangle strip constructs. Software products that implement these methods are provided.

Assessment of Haar Wavelet-Quasilinearization Technique in Heat Convection-Radiation Equations

Directory of Open Access Journals (Sweden)

Umer Saeed

2014-01-01

Full Text Available We showed that solutions by the Haar wavelet-quasilinearization technique for the two problems, namely, (i temperature distribution equation in lumped system of combined convection-radiation in a slab made of materials with variable thermal conductivity and (ii cooling of a lumped system by combined convection and radiation are strongly reliable and also more accurate than the other numerical methods and are in good agreement with exact solution. According to the Haar wavelet-quasilinearization technique, we convert the nonlinear heat transfer equation to linear discretized equation with the help of quasilinearization technique and apply the Haar wavelet method at each iteration of quasilinearization technique to get the solution. The main aim of present work is to show the reliability of the Haar wavelet-quasilinearization technique for heat transfer equations.

Wavelet Packet Transform Based Driver Distraction Level Classification Using EEG

Directory of Open Access Journals (Sweden)

Mousa Kadhim Wali

2013-01-01

Full Text Available We classify the driver distraction level (neutral, low, medium, and high based on different wavelets and classifiers using wireless electroencephalogram (EEG signals. 50 subjects were used for data collection using 14 electrodes. We considered for this research 4 distraction stimuli such as Global Position Systems (GPS, music player, short message service (SMS, and mental tasks. Deriving the amplitude spectrum of three different frequency bands theta, alpha, and beta of EEG signals was based on fusion of discrete wavelet packet transform (DWPT and FFT. Comparing the results of three different classifiers (subtractive fuzzy clustering probabilistic neural network, -nearest neighbor was based on spectral centroid, and power spectral features extracted by different wavelets (db4, db8, sym8, and coif5. The results of this study indicate that the best average accuracy achieved by subtractive fuzzy inference system classifier is 79.21% based on power spectral density feature extracted by sym8 wavelet which gave a good class discrimination under ANOVA test.

Image Denoising Using Singular Value Difference in the Wavelet Domain

Directory of Open Access Journals (Sweden)

Min Wang

2018-01-01

Full Text Available Singular value (SV difference is the difference in the singular values between a noisy image and the original image; it varies regularly with noise intensity. This paper proposes an image denoising method using the singular value difference in the wavelet domain. First, the SV difference model is generated for different noise variances in the three directions of the wavelet transform and the noise variance of a new image is used to make the calculation by the diagonal part. Next, the single-level discrete 2-D wavelet transform is used to decompose each noisy image into its low-frequency and high-frequency parts. Then, singular value decomposition (SVD is used to obtain the SVs of the three high-frequency parts. Finally, the three denoised high-frequency parts are reconstructed by SVD from the SV difference, and the final denoised image is obtained using the inverse wavelet transform. Experiments show the effectiveness of this method compared with relevant existing methods.

Experimental study on the crack detection with optimized spatial wavelet analysis and windowing

Science.gov (United States)

Ghanbari Mardasi, Amir; Wu, Nan; Wu, Christine

2018-05-01

In this paper, a high sensitive crack detection is experimentally realized and presented on a beam under certain deflection by optimizing spatial wavelet analysis. Due to the crack existence in the beam structure, a perturbation/slop singularity is induced in the deflection profile. Spatial wavelet transformation works as a magnifier to amplify the small perturbation signal at the crack location to detect and localize the damage. The profile of a deflected aluminum cantilever beam is obtained for both intact and cracked beams by a high resolution laser profile sensor. Gabor wavelet transformation is applied on the subtraction of intact and cracked data sets. To improve detection sensitivity, scale factor in spatial wavelet transformation and the transformation repeat times are optimized. Furthermore, to detect the possible crack close to the measurement boundaries, wavelet transformation edge effect, which induces large values of wavelet coefficient around the measurement boundaries, is efficiently reduced by introducing different windowing functions. The result shows that a small crack with depth of less than 10% of the beam height can be localized with a clear perturbation. Moreover, the perturbation caused by a crack at 0.85 mm away from one end of the measurement range, which is covered by wavelet transform edge effect, emerges by applying proper window functions.

Wavelet analysis deformation monitoring data of high-speed railway bridge

Science.gov (United States)

Tang, ShiHua; Huang, Qing; Zhou, Conglin; Xu, HongWei; Liu, YinTao; Li, FeiDa

2015-12-01

Deformation monitoring data of high-speed railway bridges will inevitably be affected because of noise pollution, A deformation monitoring point of high-speed railway bridge was measurd by using sokkia SDL30 electronic level for a long time,which got a large number of deformation monitoring data. Based on the characteristics of the deformation monitoring data of high-speed railway bridge, which contain lots of noise. Based on the MATLAB software platform, 120 groups of deformation monitoring data were applied to analysis of wavelet denoising.sym6,db6 wavelet basis function were selected to analyze and remove the noise.The original signal was broken into three layers wavelet,which contain high frequency coefficients and low frequency coefficients.However, high frequency coefficient have plenty of noise.Adaptive method of soft and hard threshold were used to handle in the high frequency coefficient.Then,high frequency coefficient that was removed much of noise combined with low frequency coefficient to reconstitute and obtain reconstruction wavelet signal.Root Mean Square Error (RMSE) and Signal-To-Noise Ratio (SNR) were regarded as evaluation index of denoising,The smaller the root mean square error and the greater signal-to-noise ratio indicate that them have a good effect in denoising. We can surely draw some conclusions in the experimental analysis:the db6 wavelet basis function has a good effect in wavelet denoising by using a adaptive soft threshold method,which root mean square error is minimum and signal-to-noise ratio is maximum.Moreover,the reconstructed image are more smooth than original signal denoising after wavelet denoising, which removed noise and useful signal are obtained in the original signal.Compared to the other three methods, this method has a good effect in denoising, which not only retain useful signal in the original signal, but aiso reach the goal of removing noise. So, it has a strong practical value in a actual deformation monitoring

Wavelet analysis of MR functional data from the cerebellum

Energy Technology Data Exchange (ETDEWEB)

Karen, Romero Sánchez, E-mail: alphacentauri-hp@hotmail.com, E-mail: marcos-vaquezr@hotmail.com, E-mail: isabeldgg@hotmail.com; Vásquez Reyes Marcos, A., E-mail: alphacentauri-hp@hotmail.com, E-mail: marcos-vaquezr@hotmail.com, E-mail: isabeldgg@hotmail.com; González Gómez Dulce, I., E-mail: alphacentauri-hp@hotmail.com, E-mail: marcos-vaquezr@hotmail.com, E-mail: isabeldgg@hotmail.com; Hernández López, Javier M., E-mail: javierh@fcfm.buap.mx [Faculty of Physics and Mathematics, BUAP, Puebla, Pue (Mexico); Silvia, Hidalgo Tobón, E-mail: shidbon@gmail.com [Infant Hospital of Mexico, Federico Gómez, Mexico DF. Mexico and Physics Department, Universidad Autónoma Metropolitana. Iztapalapa, Mexico DF. (Mexico); Pilar, Dies Suarez, E-mail: pilydies@yahoo.com, E-mail: neurodoc@prodigy.net.mx; Eduardo, Barragán Pérez, E-mail: pilydies@yahoo.com, E-mail: neurodoc@prodigy.net.mx [Infant Hospital of Mexico, Federico Gómez, Mexico DF. (Mexico); Benito, De Celis Alonso, E-mail: benileon@yahoo.com [Faculty of Physics and Mathematics, BUAP, Puebla, Pue. Mexico and Foundation for Development Carlos Sigüenza. Puebla, Pue. (Mexico)

2014-11-07

The main goal of this project was to create a computer algorithm based on wavelet analysis of BOLD signals, which automatically diagnosed ADHD using information from resting state MR experiments. Male right handed volunteers (infants with ages between 7 and 11 years old) were studied and compared with age matched controls. Wavelet analysis, which is a mathematical tool used to decompose time series into elementary constituents and detect hidden information, was applied here to the BOLD signal obtained from the cerebellum 8 region of all our volunteers. Statistical differences between the values of the a parameters of wavelet analysis was found and showed significant differences (p<0.02) between groups. This difference might help in the future to distinguish healthy from ADHD patients and therefore diagnose ADHD.

Wavelet analysis of MR functional data from the cerebellum

International Nuclear Information System (INIS)

Karen, Romero Sánchez; Vásquez Reyes Marcos, A.; González Gómez Dulce, I.; Hernández López, Javier M.; Silvia, Hidalgo Tobón; Pilar, Dies Suarez; Eduardo, Barragán Pérez; Benito, De Celis Alonso

2014-01-01

The main goal of this project was to create a computer algorithm based on wavelet analysis of BOLD signals, which automatically diagnosed ADHD using information from resting state MR experiments. Male right handed volunteers (infants with ages between 7 and 11 years old) were studied and compared with age matched controls. Wavelet analysis, which is a mathematical tool used to decompose time series into elementary constituents and detect hidden information, was applied here to the BOLD signal obtained from the cerebellum 8 region of all our volunteers. Statistical differences between the values of the a parameters of wavelet analysis was found and showed significant differences (p<0.02) between groups. This difference might help in the future to distinguish healthy from ADHD patients and therefore diagnose ADHD

A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum

Directory of Open Access Journals (Sweden)

Pan Liu

2017-05-01

Full Text Available This paper presents a wavelet-based Gaussian method (WGM for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF. The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum.

SeismicWaveTool: Continuous and discrete wavelet analysis and filtering for multichannel seismic data

Science.gov (United States)

Galiana-Merino, J. J.; Rosa-Herranz, J. L.; Rosa-Cintas, S.; Martinez-Espla, J. J.

2013-01-01

A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of multichannel seismic data. The considered time-frequency transforms include the continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform. The developed approaches provide a fast and precise time-frequency examination of the seismograms at different frequency bands. Moreover, filtering methods for noise, transients or even baseline removal, are implemented. The primary motivation is to support seismologists with a user-friendly and fast program for the wavelet analysis, providing practical and understandable results. Program summaryProgram title: SeismicWaveTool Catalogue identifier: AENG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENG_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 611072 No. of bytes in distributed program, including test data, etc.: 14688355 Distribution format: tar.gz Programming language: MATLAB (MathWorks Inc.) version 7.8.0.347 (R2009a) or higher. Wavelet Toolbox is required. Computer: Developed on a MacBook Pro. Tested on Mac and PC. No computer-specific optimization was performed. Operating system: Any supporting MATLAB (MathWorks Inc.) v7.8.0.347 (R2009a) or higher. Tested on Mac OS X 10.6.8, Windows XP and Vista. Classification: 13. Nature of problem: Numerous research works have developed a great number of free or commercial wavelet based software, which provide specific solutions for the analysis of seismic data. On the other hand, standard toolboxes, packages or libraries, such as the MathWorks' Wavelet Toolbox for MATLAB, offer command line functions and interfaces for the wavelet analysis of one-component signals. Thus, software usually is focused on very specific problems

Wavelets and Sentiment in the Heterogeneous Agents Model

Czech Academy of Sciences Publication Activity Database

Vácha, Lukáš; Vošvrda, Miloslav

2008-01-01

Roč. 15, č. 25 (2008), s. 41-56 ISSN 1212-074X R&D Projects: GA ČR GP402/08/P207; GA ČR GA402/07/1113; GA ČR(CZ) GA402/06/0990 Institutional research plan: CEZ:AV0Z10750506 Keywords : heterogeneous agents model * market sentiment * Hurst exponent * wavelets Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2008/E/vacha-wavelets and sentiment in the heterogeneous agents model.pdf

Controlled wavelet domain sparsity for x-ray tomography

Science.gov (United States)

Purisha, Zenith; Rimpeläinen, Juho; Bubba, Tatiana; Siltanen, Samuli

2018-01-01

Tomographic reconstruction is an ill-posed inverse problem that calls for regularization. One possibility is to require sparsity of the unknown in an orthonormal wavelet basis. This, in turn, can be achieved by variational regularization, where the penalty term is the sum of the absolute values of the wavelet coefficients. The primal-dual fixed point algorithm showed that the minimizer of the variational regularization functional can be computed iteratively using a soft-thresholding operation. Choosing the soft-thresholding parameter \

Diagnostics of detector tube impacting with wavelet techniques

Energy Technology Data Exchange (ETDEWEB)

Racz, A. [KFKI-AEKI Applied Reactor Physics, Budapest (Hungary); Pazsit, I. [Chalmers Univ. of Tech., Goeteborg (Sweden). Dept. of Reactor Physics

1997-12-08

A neutron noise based method is proposed for the detection of impacting of detector tubes in BWRs. The basic idea relies on the assumption that non-stationary transients (e.g. fuel box vibrations) may be induced at impacting. Such short-lived transients are difficult to detect by spectral analysis methods. However, their presence in the detector signal can be detected by wavelet analysis. A simple wavelet technique, the so-called Haar transform, is suggested for the detection of impacting. Tests of the proposed method have been performed with success on both simulated data with controlled impacting as well as with real measurement data. The simulation model as well as the results of the wavelet analysis are reported in this paper. The source code written in MATLAB are available at a public ftp site. The necessary information to reproduce the simulation results is also reported. (author).

Diagnostics of detector tube impacting with wavelet techniques

Energy Technology Data Exchange (ETDEWEB)

Racz, A.; Pazsit, I

1998-04-01

A neutron noise based method is proposed for the detection of impacting of detector tubes in BWRs. The basic idea relies on the assumption that non-stationary transients (e.g. fuel box vibrations) may be induced at impacting. Such short-lived transients are difficult to detect by spectral analysis methods. However, their presence in the detector signal can be detected by wavelet analysis. A simple wavelet technique, the so-called Haar transform, is suggested for the detection of impacting. Tests of the proposed method have been performed with success on both simulated data with controlled impacting as well as with real measurement data. The simulation model as well as the results of the wavelet analysis are reported in this paper. The source codes written in MATLAB[reg] are available at a public ftp site. The necessary information to reproduce the simulation results is also reported.

Wavelet regression model in forecasting crude oil price

Science.gov (United States)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

Science.gov (United States)

Lin, Yuan-Chien; Yu, Hwa-Lung

2013-04-01

The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between

Generalized exact holographic mapping with wavelets

Science.gov (United States)

Lee, Ching Hua

2017-12-01

The idea of renormalization and scale invariance is pervasive across disciplines. It has not only drawn numerous surprising connections between physical systems under the guise of holographic duality, but has also inspired the development of wavelet theory now widely used in signal processing. Synergizing on these two developments, we describe in this paper a generalized exact holographic mapping that maps a generic N -dimensional lattice system to a (N +1 )-dimensional holographic dual, with the emergent dimension representing scale. In previous works, this was achieved via the iterations of the simplest of all unitary mappings, the Haar mapping, which fails to preserve the form of most Hamiltonians. By taking advantage of the full generality of biorthogonal wavelets, our new generalized holographic mapping framework is able to preserve the form of a large class of lattice Hamiltonians. By explicitly separating features that are fundamentally associated with the physical system from those that are basis specific, we also obtain a clearer understanding of how the resultant bulk geometry arises. For instance, the number of nonvanishing moments of the high-pass wavelet filter is revealed to be proportional to the radius of the dual anti-de Sitter space geometry. We conclude by proposing modifications to the mapping for systems with generic Fermi pockets.

Analysis of Ultrasonic Transmitted Signal for Apple using Wavelet Transform

International Nuclear Information System (INIS)

Kim, Ki Bok; Lee, Sang Dae; Choi, Man Yong; Kim, Man Soo

2005-01-01

This study was conducted to analyze the ultrasonic transmitted signal for apple using wavelet transform. Fruit consists of nonlinear visco-elastic properties such as flesh, an ovary and rind and lienee most ultrasonic wave is attenuated and its frequency is shifted during passing the fruit. Thus it is not easy to evaluate the internal quality of the fruit using typical ultrasonic parameters such as wave velocity, attenuation, and frequency spectrum. The discrete wavelet transform was applied to the ultrasonic transmitted signal for apple. The magnitude of the first peak frequency of the wavelet basis from the ultrasonic transmitted signal showed a close correlation to the storage time of apple

Haar wavelets, fluctuations and structure functions: convenient choices for geophysics

Directory of Open Access Journals (Sweden)

S. Lovejoy

2012-09-01

Full Text Available Geophysical processes are typically variable over huge ranges of space-time scales. This has lead to the development of many techniques for decomposing series and fields into fluctuations Δv at well-defined scales. Classically, one defines fluctuations as differences: (Δv_diff = v(x+Δx-v(x and this is adequate for many applications (Δx is the "lag". However, if over a range one has scaling Δv ∝ Δx^H, these difference fluctuations are only adequate when 0 < H < 1. Hence, there is the need for other types of fluctuations. In particular, atmospheric processes in the "macroweather" range ≈10 days to 10–30 yr generally have −1 < H < 0, so that a definition valid over the range −1 < H < 1 would be very useful for atmospheric applications. A general framework for defining fluctuations is wavelets. However, the generality of wavelets often leads to fairly arbitrary choices of "mother wavelet" and the resulting wavelet coefficients may be difficult to interpret. In this paper we argue that a good choice is provided by the (historically first wavelet, the Haar wavelet (Haar, 1910, which is easy to interpret and – if needed – to generalize, yet has rarely been used in geophysics. It is also easy to implement numerically: the Haar fluctuation (Δv_Haar at lag Δx is simply equal to the difference of the mean from x to x+ Δx/2 and from x+Δx/2 to x+Δx. Indeed, we shall see that the interest of the Haar wavelet is this relation to the integrated process rather than its wavelet nature per se.

Using numerical multifractal simulations, we show that it is quite accurate, and we compare and contrast it with another similar technique, detrended fluctuation analysis. We find that, for estimating scaling exponents, the two methods are very similar, yet

Application of 3D wavelet transforms for crack detection in rotor ...

Indian Academy of Sciences (India)

Vijayawada 520 007. bAll India Council for Technical Education (AICTE), New Delhi 110 001 ... rotor system the transient analysis has been applied. ... In the present work a new wavelet plot called cross wavelet transform (XWT) has been.

Detection of Early Faults in Rotating Machinery Based on Wavelet Analysis

Directory of Open Access Journals (Sweden)

Meng Hee Lim

2013-01-01

Full Text Available This paper explores the application of wavelet analysis for the detection of early changes in rotor dynamics caused by common machinery faults, namely, rotor unbalance and minor blade rubbing conditions. In this paper, the time synchronised wavelet analysis method was formulated and its effectiveness to detect machinery faults at the early stage was evaluated based on signal simulation and experimental study. The proposed method provides a more standardised approach to visualise the current state of rotor dynamics of a rotating machinery by taking into account the effects of time shift, wavelet edge distortion, and system noise suppression. The experimental results showed that this method is able to reveal subtle changes of the vibration signal characteristics in both the frequency content distribution and the amplitude distortion caused by minor rotor unbalance and blade rubbing conditions. Besides, this method also appeared to be an effective tool to diagnose and to discriminate the different types of machinery faults based on the unique pattern of the wavelet contours. This study shows that the proposed wavelet analysis method is promising to reveal machinery faults at early stage as compared to vibration spectrum analysis.

A Wavelet-Based Optimization Method for Biofuel Production

Directory of Open Access Journals (Sweden)

Maurizio Carlini

2018-02-01

Full Text Available On a global scale many countries are still heavily dependent on crude oil to produce energy and fuel for transport, with a resulting increase of atmospheric pollution. A possible solution to obviate this problem is to find eco-sustainable energy sources. A potential choice could be the use of biodiesel as fuel. The work presented aims to characterise the transesterification reaction of waste peanut frying oil using colour analysis and wavelet analysis. The biodiesel production, with the complete absence of mucilages, was evaluated through a suitable set of energy wavelet coefficients and scalograms. The physical characteristics of the biodiesel are influenced by mucilages. In particular the viscosity, that is a fundamental parameter for the correct use of the biodiesel, might be compromised. The presence of contaminants in the samples can often be missed by visual analysis. The low and high frequency wavelet analysis, by investigating the energy change of wavelet coefficient, provided a valid characterisation of the quality of the samples, related to the absence of mucilages, which is consistent with the experimental results. The proposed method of this work represents a preliminary analysis, before the subsequent chemical physical analysis, that can be develop during the production phases of the biodiesel in order to optimise the process, avoiding the presence of impurities in suspension in the final product.

An NMR log echo data de-noising method based on the wavelet packet threshold algorithm

International Nuclear Information System (INIS)

Meng, Xiangning; Xie, Ranhong; Li, Changxi; Hu, Falong; Li, Chaoliu; Zhou, Cancan

2015-01-01

To improve the de-noising effects of low signal-to-noise ratio (SNR) nuclear magnetic resonance (NMR) log echo data, this paper applies the wavelet packet threshold algorithm to the data. The principle of the algorithm is elaborated in detail. By comparing the properties of a series of wavelet packet bases and the relevance between them and the NMR log echo train signal, ‘sym7’ is found to be the optimal wavelet packet basis of the wavelet packet threshold algorithm to de-noise the NMR log echo train signal. A new method is presented to determine the optimal wavelet packet decomposition scale; this is within the scope of its maximum, using the modulus maxima and the Shannon entropy minimum standards to determine the global and local optimal wavelet packet decomposition scales, respectively. The results of applying the method to the simulated and actual NMR log echo data indicate that compared with the wavelet threshold algorithm, the wavelet packet threshold algorithm, which shows higher decomposition accuracy and better de-noising effect, is much more suitable for de-noising low SNR–NMR log echo data. (paper)

Discrete wavelet transform: a tool in smoothing kinematic data.

Science.gov (United States)

Ismail, A R; Asfour, S S

1999-03-01

Motion analysis systems typically introduce noise to the displacement data recorded. Butterworth digital filters have been used to smooth the displacement data in order to obtain smoothed velocities and accelerations. However, this technique does not yield satisfactory results, especially when dealing with complex kinematic motions that occupy the low- and high-frequency bands. The use of the discrete wavelet transform, as an alternative to digital filters, is presented in this paper. The transform passes the original signal through two complementary low- and high-pass FIR filters and decomposes the signal into an approximation function and a detail function. Further decomposition of the signal results in transforming the signal into a hierarchy set of orthogonal approximation and detail functions. A reverse process is employed to perfectly reconstruct the signal (inverse transform) back from its approximation and detail functions. The discrete wavelet transform was applied to the displacement data recorded by Pezzack et al., 1977. The smoothed displacement data were twice differentiated and compared to Pezzack et al.'s acceleration data in order to choose the most appropriate filter coefficients and decomposition level on the basis of maximizing the percentage of retained energy (PRE) and minimizing the root mean square error (RMSE). Daubechies wavelet of the fourth order (Db4) at the second decomposition level showed better results than both the biorthogonal and Coiflet wavelets (PRE = 97.5%, RMSE = 4.7 rad s-2). The Db4 wavelet was then used to compress complex displacement data obtained from a noisy mathematically generated function. Results clearly indicate superiority of this new smoothing approach over traditional filters.

Object-Oriented Wavelet-Layered Digital Watermarking Technique

Institute of Scientific and Technical Information of China (English)

LIU Xiao-yun; YU Jue-bang; LI Ming-yu

2005-01-01

In this paper, an object-oriented digital watermarking technique is proposed in the wavelet domain for still images. According to the difference of recognition degree of the human eye to the different region of the image, the image is divided into the interested region and uninterested region of human eye vision in this scheme. Using the relativity of position and the difference to ocular sensitivity of the multiresolution wavelet among each subband, the image is processed with layered watermarking append technique. Experimental results show that the proposed technique successfully survives image processing operations, additive noise and JPEG compression.

A Hybrid Model Based on Wavelet Decomposition-Reconstruction in Track Irregularity State Forecasting

Directory of Open Access Journals (Sweden)

Chaolong Jia

2015-01-01

Full Text Available Wavelet is able to adapt to the requirements of time-frequency signal analysis automatically and can focus on any details of the signal and then decompose the function into the representation of a series of simple basis functions. It is of theoretical and practical significance. Therefore, this paper does subdivision on track irregularity time series based on the idea of wavelet decomposition-reconstruction and tries to find the best fitting forecast model of detail signal and approximate signal obtained through track irregularity time series wavelet decomposition, respectively. On this ideology, piecewise gray-ARMA recursive based on wavelet decomposition and reconstruction (PG-ARMARWDR and piecewise ANN-ARMA recursive based on wavelet decomposition and reconstruction (PANN-ARMARWDR models are proposed. Comparison and analysis of two models have shown that both these models can achieve higher accuracy.

Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings

Science.gov (United States)

Wang, Dong; Zhao, Yang; Yi, Cai; Tsui, Kwok-Leung; Lin, Jianhui

2018-02-01

Rolling element bearings are widely used in various industrial machines, such as electric motors, generators, pumps, gearboxes, railway axles, turbines, and helicopter transmissions. Fault diagnosis of rolling element bearings is beneficial to preventing any unexpected accident and reducing economic loss. In the past years, many bearing fault detection methods have been developed. Recently, a new adaptive signal processing method called empirical wavelet transform attracts much attention from readers and engineers and its applications to bearing fault diagnosis have been reported. The main problem of empirical wavelet transform is that Fourier segments required in empirical wavelet transform are strongly dependent on the local maxima of the amplitudes of the Fourier spectrum of a signal, which connotes that Fourier segments are not always reliable and effective if the Fourier spectrum of the signal is complicated and overwhelmed by heavy noises and other strong vibration components. In this paper, sparsity guided empirical wavelet transform is proposed to automatically establish Fourier segments required in empirical wavelet transform for fault diagnosis of rolling element bearings. Industrial bearing fault signals caused by single and multiple railway axle bearing defects are used to verify the effectiveness of the proposed sparsity guided empirical wavelet transform. Results show that the proposed method can automatically discover Fourier segments required in empirical wavelet transform and reveal single and multiple railway axle bearing defects. Besides, some comparisons with three popular signal processing methods including ensemble empirical mode decomposition, the fast kurtogram and the fast spectral correlation are conducted to highlight the superiority of the proposed method.

Construction of Interval Wavelet Based on Restricted Variational Principle and Its Application for Solving Differential Equations

OpenAIRE

Mei, Shu-Li; Lv, Hong-Liang; Ma, Qin

2008-01-01

Based on restricted variational principle, a novel method for interval wavelet construction is proposed. For the excellent local property of quasi-Shannon wavelet, its interval wavelet is constructed, and then applied to solve ordinary differential equations. Parameter choices for the interval wavelet method are discussed and its numerical performance is demonstrated.

Multifractal Cross Wavelet Analysis

Science.gov (United States)

Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.

Multi-dimensional medical images compressed and filtered with wavelets

International Nuclear Information System (INIS)

Boyen, H.; Reeth, F. van; Flerackers, E.

2002-01-01

Full text: Using the standard wavelet decomposition methods, multi-dimensional medical images can be compressed and filtered by repeating the wavelet-algorithm on 1D-signals in an extra loop per extra dimension. In the non-standard decomposition for multi-dimensional images the areas that must be zero-filled in case of band- or notch-filters are more complex than geometric areas such as rectangles or cubes. Adding an additional dimension in this algorithm until 4D (e.g. a 3D beating heart) increases the geometric complexity of those areas even more. The aim of our study was to calculate the boundaries of the formed complex geometric areas, so we can use the faster non-standard decomposition to compress and filter multi-dimensional medical images. Because a lot of 3D medical images taken by PET- or SPECT-cameras have only a few layers in the Z-dimension and compressing images in a dimension with a few voxels is usually not worthwhile, we provided a solution in which one can choose which dimensions will be compressed or filtered. With the proposal of non-standard decomposition on Daubechies' wavelets D2 to D20 by Steven Gollmer in 1992, 1D data can be compressed and filtered. Each additional level works only on the smoothed data, so the transformation-time halves per extra level. Zero-filling a well-defined area alter the wavelet-transform and then performing the inverse transform will do the filtering. To be capable to compress and filter up to 4D-Images with the faster non-standard wavelet decomposition method, we have investigated a new method for calculating the boundaries of the areas which must be zero-filled in case of filtering. This is especially true for band- and notch filtering. Contrary to the standard decomposition method, the areas are no longer rectangles in 2D or cubes in 3D or a row of cubes in 4D: they are rectangles expanded with a half-sized rectangle in the other direction for 2D, cubes expanded with half cubes in one and quarter cubes in the

Two-dimensional wavelet transform for reliability-guided phase unwrapping in optical fringe pattern analysis.

Science.gov (United States)

Li, Sikun; Wang, Xiangzhao; Su, Xianyu; Tang, Feng

2012-04-20

This paper theoretically discusses modulus of two-dimensional (2D) wavelet transform (WT) coefficients, calculated by using two frequently used 2D daughter wavelet definitions, in an optical fringe pattern analysis. The discussion shows that neither is good enough to represent the reliability of the phase data. The differences between the two frequently used 2D daughter wavelet definitions in the performance of 2D WT also are discussed. We propose a new 2D daughter wavelet definition for reliability-guided phase unwrapping of optical fringe pattern. The modulus of the advanced 2D WT coefficients, obtained by using a daughter wavelet under this new daughter wavelet definition, includes not only modulation information but also local frequency information of the deformed fringe pattern. Therefore, it can be treated as a good parameter that represents the reliability of the retrieved phase data. Computer simulation and experimentation show the validity of the proposed method.

Decompositions of bubbly flow PIV velocity fields using discrete wavelets multi-resolution and multi-section image method

International Nuclear Information System (INIS)

Choi, Je-Eun; Takei, Masahiro; Doh, Deog-Hee; Jo, Hyo-Jae; Hassan, Yassin A.; Ortiz-Villafuerte, Javier

2008-01-01

Currently, wavelet transforms are widely used for the analyses of particle image velocimetry (PIV) velocity vector fields. This is because the wavelet provides not only spatial information of the velocity vectors, but also of the time and frequency domains. In this study, a discrete wavelet transform is applied to real PIV images of bubbly flows. The vector fields obtained by a self-made cross-correlation PIV algorithm were used for the discrete wavelet transform. The performances of the discrete wavelet transforms were investigated by changing the level of power of discretization. The images decomposed by wavelet multi-resolution showed conspicuous characteristics of the bubbly flows for the different levels. A high spatial bubble concentrated area could be evaluated by the constructed discrete wavelet transform algorithm, in which high-leveled wavelets play dominant roles in revealing the flow characteristics

Image Registration Using Redundant Wavelet Transforms

National Research Council Canada - National Science Library

Brown, Richard

2001-01-01

.... In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and improve processing efficiency...

A Wavelet-Based Algorithm for the Spatial Analysis of Poisson Data

Science.gov (United States)

Freeman, P. E.; Kashyap, V.; Rosner, R.; Lamb, D. Q.

2002-01-01

Wavelets are scalable, oscillatory functions that deviate from zero only within a limited spatial regime and have average value zero, and thus may be used to simultaneously characterize the shape, location, and strength of astronomical sources. But in addition to their use as source characterizers, wavelet functions are rapidly gaining currency within the source detection field. Wavelet-based source detection involves the correlation of scaled wavelet functions with binned, two-dimensional image data. If the chosen wavelet function exhibits the property of vanishing moments, significantly nonzero correlation coefficients will be observed only where there are high-order variations in the data; e.g., they will be observed in the vicinity of sources. Source pixels are identified by comparing each correlation coefficient with its probability sampling distribution, which is a function of the (estimated or a priori known) background amplitude. In this paper, we describe the mission-independent, wavelet-based source detection algorithm ``WAVDETECT,'' part of the freely available Chandra Interactive Analysis of Observations (CIAO) software package. Our algorithm uses the Marr, or ``Mexican Hat'' wavelet function, but may be adapted for use with other wavelet functions. Aspects of our algorithm include: (1) the computation of local, exposure-corrected normalized (i.e., flat-fielded) background maps; (2) the correction for exposure variations within the field of view (due to, e.g., telescope support ribs or the edge of the field); (3) its applicability within the low-counts regime, as it does not require a minimum number of background counts per pixel for the accurate computation of source detection thresholds; (4) the generation of a source list in a manner that does not depend upon a detailed knowledge of the point spread function (PSF) shape; and (5) error analysis. These features make our algorithm considerably more general than previous methods developed for the

Wavelet Packet Entropy in Speaker-Independent Emotional State Detection from Speech Signal

OpenAIRE

Mina Kadkhodaei Elyaderani; Seyed Hamid Mahmoodian; Ghazaal Sheikhi

2015-01-01

In this paper, wavelet packet entropy is proposed for speaker-independent emotion detection from speech. After pre-processing, wavelet packet decomposition using wavelet type db3 at level 4 is calculated and Shannon entropy in its nodes is calculated to be used as feature. In addition, prosodic features such as first four formants, jitter or pitch deviation amplitude, and shimmer or energy variation amplitude besides MFCC features are applied to complete the feature vector. Then, Support Vect...

Response of Autonomic Nervous System to Body Positions: Fourier and Wavelet Analysis

OpenAIRE

Xu, Aiguo; Gonnella, G.; Federici, A.; Stramaglia, S.; Simone, F.; Zenzola, A.; Santostasi, R.

2003-01-01

Two mathematical methods, the Fourier and wavelet transforms, were used to study the short term cardiovascular control system. Time series, picked from electrocardiogram and arterial blood pressure lasting 6 minutes, were analyzed in supine position (SUP), during the first (HD1), and the second parts (HD2) of $90^{\\circ}$ head down tilt and during recovery (REC). The wavelet transform was performed using the Haar function of period $T=2^j$ ($% j=1$,2,$... $,6) to obtain wavelet coefficients. ...

Wavelet neural network load frequency controller

International Nuclear Information System (INIS)

Hemeida, Ashraf Mohamed

2005-01-01

This paper presents the feasibility of applying a wavelet neural network (WNN) approach for the load frequency controller (LFC) to damp the frequency oscillations of two area power systems due to load disturbances. The present intelligent control system trained the wavelet neural network (WNN) controller on line with adaptive learning rates, which are derived in the sense of a discrete type Lyapunov stability theorem. The present WNN controller is designed individually for each area. The proposed technique is applied successfully for a wide range of operating conditions. The time simulation results indicate its superiority and effectiveness over the conventional approach. The effects of consideration of the governor dead zone on the system performance are studied using the proposed controller and the conventional one

Implementation of Wavelet-Based Robust Differential Control for Electric Vehicle Application

DEFF Research Database (Denmark)

Daya, Febin; Padmanaban, Sanjeevikumar; Blaabjerg, Frede

2015-01-01

This research letter presents the modeling and simulation of electronic differential, employing a novel wavelet controller for two brushless dc motors. The proposed controller uses discrete wavelet transform to decompose the error between actual and reference speed. Error signal that is actually...

Pricing early-exercise and discrete barrier options by Shannon wavelet expansions

NARCIS (Netherlands)

Maree, S. C.; Ortiz-Gracia, L.; Oosterlee, C. W.

2017-01-01

We present a pricing method based on Shannon wavelet expansions for early-exercise and discretely-monitored barrier options under exponential L,vy asset dynamics. Shannon wavelets are smooth, and thus approximate the densities that occur in finance well, resulting in exponential convergence.

A wavelet analysis of co-movements in Asian gold markets

Science.gov (United States)

Das, Debojyoti; Kannadhasan, M.; Al-Yahyaee, Khamis Hamed; Yoon, Seong-Min

2018-02-01

This study assesses the cross-country co-movements of gold spot returns among the major gold consuming countries in Asia using wavelet-based analysis for a dataset spanning over 26 years. Wavelet-based analysis is used since it allows measuring co-movements in a time-frequency space. The results suggest intense and positive co-movements in Asia after the Asian financial crisis of 1997 at all frequencies. In addition, the Asian gold spot markets depict a state of impending perfect market integration. Finally, Thailand emerges as the potential market leader in all wavelet scales except one, which is led by India. The study has important implications for international diversification of a single-asset (gold) portfolio.

Wavelet Filtering to Reduce Conservatism in Aeroservoelastic Robust Stability Margins

Science.gov (United States)

Brenner, Marty; Lind, Rick

1998-01-01

Wavelet analysis for filtering and system identification was used to improve the estimation of aeroservoelastic stability margins. The conservatism of the robust stability margins was reduced with parametric and nonparametric time-frequency analysis of flight data in the model validation process. Nonparametric wavelet processing of data was used to reduce the effects of external desirableness and unmodeled dynamics. Parametric estimates of modal stability were also extracted using the wavelet transform. Computation of robust stability margins for stability boundary prediction depends on uncertainty descriptions derived from the data for model validation. F-18 high Alpha Research Vehicle aeroservoelastic flight test data demonstrated improved robust stability prediction by extension of the stability boundary beyond the flight regime.

Feature Extraction on Brain Computer Interfaces using Discrete Dyadic Wavelet Transform: Preliminary Results

International Nuclear Information System (INIS)

Gareis, I; Gentiletti, G; Acevedo, R; Rufiner, L

2011-01-01

The purpose of this work is to evaluate different feature extraction alternatives to detect the event related evoked potential signal on brain computer interfaces, trying to minimize the time employed and the classification error, in terms of sensibility and specificity of the method, looking for alternatives to coherent averaging. In this context the results obtained performing the feature extraction using discrete dyadic wavelet transform using different mother wavelets are presented. For the classification a single layer perceptron was used. The results obtained with and without the wavelet decomposition were compared; showing an improvement on the classification rate, the specificity and the sensibility for the feature vectors obtained using some mother wavelets.