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25th signal processing and Communications applications Conference (SIU)

作者： Konyarl, M. Zeki Erturk, Sarp Kocaeli Univ Bilisim Sistemleri Muhendisligi Bolumu Izmit Turkey Kocaeli Univ Elekt & Haberlesme Muhendisligi Bolumu Izmit Turkey

ISBN: (纸本)9781509064946

Human visual system detects details in coloured images better. Sometimes interpretation of details in gray scale ultrasound images becomes harder. So in this work pseudocoloring of ultrasound images using empirical mode decomposition (EMD) is proposed. EMD doesn't use base function so it has more advantages than Fourier and wavelet transforms. The proposed method pseudocolored image by assigning two dimensional images to red, green and blue color channels. The images obtained by the proposed method are more preferred when compared with the results in the literature.

关键词： empirical mode decomposition pseudocolor ultrasound image

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DWT-SVD and DCT based robust and blind watermarking scheme for copyright protection

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MULTIMEDIA TOOLS AND applications 2017年第11期76卷 13001-13024页

作者： Singh, Durgesh Singh, Sanjay K. Indian Inst Technol BHU Dept Comp Sci & Engn Varanasi 221005 Uttar Pradesh India

In this article, a new DWT-SVD and DCT with Arnold Cat Map encryption based robust and blind watermarking scheme is proposed for copyright protection. The proposed scheme solves the most frequently occurring watermarking security problems in Singular Value Decomposition (SVD) based schemes which are unauthorized reading and false-positive detection. This scheme also optimizes fidelity and robustness characteristics. The grey image watermark splits into two parts using four bits MSBs and four bits LSBs of each pixel. Discrete Cosine Transform (DCT) coefficients of these MSBs and LSBs values are embedded into the middle singular value of each block having size 4 x 4 of the host image's one level Discrete wavelet Transform (DWT) sub-bands. The reason for incorporating Arnold Cat Map in the proposed scheme is to encode the watermark image before embedding it in the host image. The proposed scheme is a blind scheme and does not require the choice of scaling factor. Thus, the proposed scheme is secure as well as free from the false positive detection problem. The proposed watermarking scheme is tested for various malicious and non-malicious attacks. The experimental results demonstrate that the scheme is robust, imperceptible and secure to several attacks and common signal processing operations.

关键词： Digital image watermarking False positive detection problem Discrete wavelet transform Singular value decomposition Arnold cat map Discrete cosine transform

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ACCELERATING DISCRETE wavelet TRANSFORMS ON GPUS 24

ACCELERATING DISCRETE WAVELET TRANSFORMS ON GPUS

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24th IEEE International Conference on image processing (ICIP)

作者： Barina, David Kula, Michal Matysek, Michal Zemcik, Pavel Brno Univ Technol Fac Informat Technol Brno Czech Republic

ISBN: (纸本)9781509021758

The two-dimensional discrete wavelet transform has a huge number of applications in image-processing techniques. Until now, several papers compared the performance of such transform on graphics processing units (GPUs). However, all of them only dealt with lifting and convolution computation schemes. In this paper, we show that corresponding horizontal and vertical lifting parts of the lifting scheme can be merged into non-separable lifting units, which halves the number of steps. We also discuss an optimization strategy leading to a reduction in the number of arithmetic operations. The schemes were assessed using the OpenCL and pixel shaders. The proposed non-separable lifting scheme outperforms the existing schemes in many cases, irrespective of its higher complexity.

关键词： Discrete wavelet transform image processing synchronization graphics processors

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wavelet-based aortic annulus sizing of echocardiography images 5

Wavelet-based aortic annulus sizing of echocardiography imag...

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5th IEEE International Conference on signal and image processing applications, ICSIPA 2017

作者： Mohammad, Norhasmira Omar, Zaid Sheikh, Usman Ullah Rahman, Ab Al-Hadi Ab Sahrim, Mus'Ab Faculty of Bioscience and Medical Engineering Universiti Teknologi Malaysia Skudai Johor Bahru81310 Malaysia Bandar Baru Nilai Nilai Negeri Sembilan71800 Malaysia

ISBN: (纸本)9781509055593

Aortic stenosis (AS) is a condition where the calcification deposit within the heart leaflets narrows the valve and restricts the blood from flowing through it. This disease is progressive over time where it may affect the mechanism of the heart valve. To alleviate this condition without resorting to surgery, which runs the risk of mortality, a new method of treatment has been introduced: Transcatheter Aortic Valve Implantation (TAVI), in which imagery acquired from real-Time echocardiogram (Echo) are needed to determine the exact size of aortic annulus. However, Echo data often suffers from speckle noise and low pixel resolution, which may result in incorrect sizing of the annulus. Our study therefore aims to perform an automated detection and measurement of aortic annulus size from Echo imagery. Two stages of algorithm are presented-image denoising and object detection. For the removal of speckle noise, wavelet thresholding technique is applied. It consists of three sequential steps;applying linear discrete wavelet transform, thresholding wavelet coefficients and performing linear inverse wavelet transform. For the next stage of analysis, several morphological operations are used to perform object detection as well as valve sizing. The results showed that the automated system is able to produce more accurate sizing based on ground truth. © 2017 IEEE.

关键词： Object detection

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Role of Genetic Algorithm in Performance Improvement of image Steganography combined with Transform and Its Hybrid wavelet 2

Role of Genetic Algorithm in Performance Improvement of Imag...

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2nd International Conference on Communication Systems, Computing and IT applications (CSCITA)

作者： Joshi, Shweta Sonawane, Kavita V. Khan, Shamsuddin St Francis Inst Technol Dept Comp Engn Mumbai 103 Maharashtra India

ISBN: (纸本)9781509043811

This paper proposes an image steganography for hiding secret images. The objective of the proposed work is to increase the embedding capacity while ensuring the security of the image. This has been addressed using two levels of processing. First is the application of Genetic Algorithm (GA) as 'before embedding hiding technique' which tries to identify suitable places in cover image where embedding of secret image will not lead to much distortion in the image. Second process is improvement using Discrete Cosine Transform (DCT) and its wavelet (DCWT) to gain the advantage of their energy compaction property. The secret image is embedded in the lower energy transformed regions of the cover image. The paper makes a comparison between DCT and DCWT (with and without using GA). The experimental results are evaluated using various performance evaluation parameters such as Mean Square Error (MSE), Peak signal-to-Noise Ratio (PSNR) and Correlation. The overall comparison proves that both DCT and DCWT perform better when combined with genetic algorithm. This work also proves that the proposed two level processing contributes in improvement of both security as well as embedding capacity for the image steganography.

关键词： Steganography Genetic Algorithm DCT wavelet Secure Communication Cover image Stego image MSE PSNR Correlation

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Permuted Cubes wavelet Thresholding for Mask-Sensed MRI 22

Permuted Cubes Wavelet Thresholding for Mask-Sensed MRI

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2017 22nd International Conference on Digital signal processing (DSP)

作者： Schmale, Sebastian Seidel, Pascal Paul, Steffen Univ Bremen Inst Electrodynam & Microelect ITEM Me Otto Hahn Allee 1 D-28359 Bremen Germany

ISBN: (纸本)9781538618950

In this work we present a novel inpainting algorithm to gain reduced acquisition time and high quality data reconstruction for MRI applications. We analyzed MRI recordings of two synthetically generated and of one real measured data set. On the basis of the proposed mask-based sampling trajectories, patients only have to spend a fraction of the recording time in the MRI. Especially, in the range of high k-space coefficient reduction, the reconstruction quality of our Permuted Cubes wavelet Thresholding (PCWT) approach can compete with standard data compression-focused methods like JPEG2000 or MPEG4. In all simulations, the proposed algorithm also outperforms state-of-the-art techniques such as BM3D-MRI with respect to accuracy after data reconstruction. Regarding the quality of the approximated MRI data, we mainly focus on the clear recovery of sharp edges without undesirable artifacts and the identification of tumors within MRI frames.

关键词： image reconstruction wavelet transforms Transform coding Trajectory Standards

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Biometric Cryptosystem Scheme for Internet of Things using Fuzzy Commitment principle

Biometric Cryptosystem Scheme for Internet of Things using F...

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

作者： Atef Bentahar Abdallah Meraoumia Hakim Bendjenna Salim Chitroub Abdelhakim Zeroual LAboratory of Mathematics Informatics and Systems (LAMIS) University of Larbi Tebessi Tebessa ALGERIA LISIC Laboratory Telecommunication Department USTHB BP. 32 El-Alia Bab-Ezzouar Algiers ALGERIA

ISBN: (纸本)9781538671214;9781538671207

Recently, the ensuring security by biometric authentication/identification presents a big challenge for network designers. This precious biometric information have to be itself protected against fraudulent uses, especially during the remote authentication and data exchange in wireless mesh networks such as the Internet of Things (IoT). This paper presents a securing biometric cryptosystem for IoT based on fuzzy commitment principle which is suitable of the connected things due to their low processing and memorization capacity. Our scheme, which is based on fingerprint modalities, can be decomposed into two parts. Firstly, at the sender side, a biometric feature vector is extracted using DWT technique and then the data is encrypted in order to transmit via internet. Secondly, at the receiver side, an authentication protocol was used to authenticate the things and decrypt the received data. The obtained results, using a popular fingerprint dataset, show that the proposed scheme is more secure, fast and points at increased authentication accuracy.

关键词： Cryptography Fingerprint recognition Authentication Feature extraction Discrete wavelet transforms Internet of Things

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Nonlinear Quantization Method for wavelet-Based Video Codec

Nonlinear Quantization Method for Wavelet-Based Video Codec

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Engineering and Telecommunication (EnT-MIPT)

作者： Dam Trong Nam Gennady Yu. Gryzov Alexander V. Dvorkovich Viktor P. Dvorkovich Multimedia Systems and Technology Lab. Moscow Institute of Physics and Technology Moscow Russian Federation MIPT-School of Radio Engineering and Computer Technology Moscow Institute of Physics and Technology Moscow Russian Federation Multimedia Technology and Telecommunication Dep. Moscow Institute of Physics and Technology Moscow Russian Federation

ISBN: (纸本)9781728104331

This paper is dedicated to the research and development of quantization methods for wavelet-based video codec. Uniform, nonlinear quantization method and their potential applications for wavelet-based video codec Dirac have been investigated. The optimized quantization method for wavelet-based video codec have been proposed based on analysis of the processing results for various video types using quantization methods mentioned above. The processing results for various types of video show that the proposed method provides up to 4.2% bitrate saving for low distortion level in the intra-frame coding mode, up to 9.8% bitrate reduction for low distortion level and up to 11.2% bitrate saving for medium (acceptable) distortion level in the inter-frame coding mode compared to the uniform quantization method implemented in video codec Dirac.

关键词： Quantization (signal) Video codecs wavelet transforms Distortion Bit rate image coding

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image Super Resolution Using Fractional Discrete wavelet Transformand Fractional Fast Fourier Transform

Image Super Resolution Using Fractional Discrete Wavelet Tra...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Anita Ray Choudhury Vijay R. Dahake Department of Electronics and Telecommunication RamaraoAdik Institute of Tehnology Nerul Navi Mumbai Maharashtra

ISBN: (纸本)9781538614433;9781538614426

Super-resolution (SR) technique reconstructs a higher-resolution image or sequence from the observed LR images. In various image processing fields super resolution is playing a very crucial part. The single-frame as well as multi-frame both the methods in SR are widely used in multiple day to day applications and systems from last few years. In this work, we are proposing an image resolution enhancement technique which has its basis on interpolation of the high-frequency sub-band images obtained by fractional discrete wavelet transform (FDWT). HereFDWT is used to decompose an input low-resolution image into different subbands. Then, interpolation between the high-frequency subband images and the input image takes place, followed by combining all these images to generate a new high-resolution image by using inverse FDWT. Directional selectivity which is provided by FDWT actually produces resolution enhancement, where the high-frequency subbands in different directions contribute to the sharpness of the high-frequency details such as edges. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional bicubic interpolation image resolution enhancement techniques.

关键词： Discrete wavelet transforms Interpolation signal resolution Spatial resolution

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FOREGROUND DETECTION IN CAMOUFLAGED SCENES 24

FOREGROUND DETECTION IN CAMOUFLAGED SCENES

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24th IEEE International Conference on image processing (ICIP)

作者： Li, Shuai Florencio, Dinei Zhao, Yaqin Cook, Chris Li, Wanqing Univ Wollongong Wollongong NSW Australia Microsoft Res Redmond WA USA Nanjing Forestry Univ Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781509021758

Foreground detection has been widely studied for decades due to its importance in many practical applications. Most of the existing methods assume foreground and background show visually distinct characteristics and thus the foreground can be detected once a good background model is obtained. However, there are many situations where this is not the case. Of particular interest in video surveillance is the camouflage case. For example, an active attacker camouflages by intentionally wearing clothes that are visually similar to the background. In such cases, even given a decent background model, it is not trivial to detect foreground objects. This paper proposes a texture guided weighted voting (TGWV) method which can efficiently detect foreground objects in camouflaged scenes. The proposed method employs the stationary wavelet transform to decompose the image into frequency bands. We show that the small and hardly noticeable differences between foreground and background in the image domain can be effectively captured in certain wavelet frequency bands. To make the final foreground decision, a weighted voting scheme is developed based on intensity and texture of all the wavelet bands with weights carefully designed. Experimental results demonstrate that the proposed method achieves superior performance compared to the current state-of-the-art results.

关键词： Foreground detection background subtraction camouflaged scenes wavelet transform

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