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Single change detection-based moving object segmentation by using Daubechies complex wavelet transform

IET image processing 2014年第6期8卷 334-344页

作者： Khare, Manish Srivastava, Rajneesh Kumar Khare, Ashish Univ Allahabad Dept Elect & Commun Allahabad 211002 Uttar Pradesh India

Research in motion analysis is a challenging field and it has a variety of video surveillance applications. For any video surveillance application, background detection and removal plays an important role in segmentation of the moving objects. This study proposes a new method for segmentation of the moving object, which is based on single change detection applied on Daubechies complex wavelet coefficients of two consecutive frames. The authors have chosen Daubechies complex wavelet transform as it is shift invariant and has a better directional selectivity as compared with real-valued wavelet transforms. Single change detection is a method to obtain video object plane by inter-frame difference of two consecutive frames, and it provides automatic detection of appearances of new objects. The proposed method does not require any other parameter except wavelet coefficients. Segmentation results of the moving objects after applying the proposed method are compared with those obtained after applying other spatial and wavelet domain segmentation methods in terms of visual performance and a number of quantitative measures viz misclassification penalty, relative position-based measure, structural content, normalised absolute error and average difference and the proposed method is found better than the other methods.

关键词： directional selectivity real-valued wavelet transforms visual performance image motion analysis misclassification penalty Daubechies complex wavelet transform video signal processing object appearances Computer vision and image processing techniques relative position-based measure Optical, image and video signal processing background detection automatic detection spatial domain segmentation Integral transforms image segmentation motion analysis quantitative measures video object plane video surveillance inter-frame difference moving object segmentation object detection wavelet transforms shift invariant wavelet domain segmentation Daubechies complex wavelet coefficients single change detection Video signal processing structural content normalised absolute error video surveillance applications

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image Denoising Using Multiresolution Singular Value Decomposition Transform

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Procedia Computer Science 2015年 46卷 1708-1715页

作者： S. Malini R.S. Moni Marian Engineering College Trivandrum (Center: LBS Institute) 695 582 India

images are often corrupted by noise. For visual quality as well as for satisfactory extraction of important features from the images, denoising of the images is necessary. It is an unavoidable pre-processing step for many applications such as image compression, segmentation, identification, fusion, object recognition etc. Many successful algorithms have been proposed over the past few decades for image denoising. A recent development in this area of research is the use of multiresolution principles. wavelet decomposition and denoising are milestones in multiresolution image signal processing. In this paper, multiresolution singular value decomposition is proposed as a new method for denoising of images. The new algorithm and its implementation using MATLAB is presented. Results show that it is a good method for image denoising.

关键词： image denoising multiresolution multiresolution svd sub bands thresholding

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Robust grayscale watermarking technique based on face detection

Robust grayscale watermarking technique based on face detect...

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IEEE signal processing and Communications applications (SIU)

作者： Lauri Laur Morteza Daneshmand Mary Agoyi Gholamreza Anbarjafari Institute of Computer Science University of Tartu Tartu Estonia iCV Group University of Tartu Tartu Estonia Faculty of Engineering Cyprus International University Turkey

Due to increase of usage of digital media distributed over the Internet, concerns about security and piracy have emerged. The amount of digital media reproduction has brought a need for content watermarking. In this paper robust grayscale watermarking technique based on face detection is proposed. Face detection algorithm is used to find a face on host image and this part of image is transformed into frequency domain using Discrete wavelet Transform. Chirp z-transform is applied on low-frequency subband from previous step and LU decomposition is used on the outcome. Diagonal matrix from LU decomposition is further decomposed using Singular Value Decomposition and watermark is embedded into singular values. Numerous experiments are run on that algorithm and results are compared with novel and state-of-the-art techniques. The results show that proposed method has good imperceptibility and robustness characteristics.

关键词： Watermarking Robustness Chirp Cameras Face Transform coding Discrete wavelet transforms

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Remote sensing image super-resolution: Challenges and approaches

Remote sensing image super-resolution: Challenges and approa...

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International Conference on Digital signal processing (DSP)

作者： Daiqin Yang Zimeng Li Yatong Xia Zhenzhong Chen School of Remote Sensing and Information Engineering Wuhan University China

ISBN: (纸本)9781479980598

Remote sensing has a growing relevance in the modern society with the development of image processing of satellite imagery. However, due to the limitations of the current imaging sensors and the complex atmospheric conditions, we are facing great challenges in the remote sensing applications due to the limited spatial, spectral, radiometric and temporal resolutions. Therefore, super-resolution techniques have attracted much attention by which the low quality low resolution remote sensing images are enhanced. In this paper, we discuss the challenges in remote sensing image super-resolution and thereafter review the relevant approaches. More specifically, the different categories of remote sensing techniques, i.e., the learning-based, interpolation based, frequency domain based, and probability based methods, are reviewed and discussed. Furthermore, the super-resolution applications are discussed and insightful comments on future research directions are provided.

关键词： image reconstruction Remote sensing Interpolation Spatial resolution signal resolution wavelet transforms

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image compression techniques in Wireless Multimedia Sensor Networks

Image compression techniques in Wireless Multimedia Sensor N...

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IEEE signal processing and Communications applications (SIU)

作者： Arafat Şentürk Zehra Karapinar Resul Kara Bilgisayar Mühendisliği Bölümü Düzce Üniversitesi Düzce Türkiye

Wireless Multimedia Sensor Networks (WMSNs) provide realization of applications which is usable everywhere and address to many fields like mobile health care, environmental surveillance and traffic monitoring. Amount of data causes to traffic in memory resources, difficulties in operation, and excessive power consumption - which is the most important one- for every node while WMSNs transfer multimedia data during those applications. That kind of problems is vital for WMSNs which already have limited resources. image compression can be one of the effective solutions to overcome those problems. Thus, network lifetime of WMSNs can be increased significantly and the bandwidth can be used in a more effective manner. The main purpose of this study is to investigate image compression algorithms used for WMSNs in the literature in terms of their advantages and disadvantages after giving brief information about WMSNs.

关键词： image coding Wireless sensor networks Discrete cosine transforms Multimedia communication Transform coding Discrete wavelet transforms Algorithm design and analysis

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Sparse image and signal processing : wavelets and related geometric multiscale analysis / Second...

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2015年

作者： Starck J.-L.

来源：内蒙古大学图书馆图书评论

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SAR image despeckling and compression using K-nearest neighbour based lee filter and wavelet

SAR image despeckling and compression using K-nearest neighb...

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Congress on image and signal processing, CISP

作者： Aiyeola Sikiru Yommy Rongke Liu Spencer Ojogba Onuh Ani Cosmas Ikechukwu Beihang University Beijing P.R. China National Space Research and Development Agency Abuja Nigeria University of Nigeria Nsukka Nigeria

Synthetic Aperture Radar (SAR) is an important tool for obtaining information from the surface of the Earth with the capability of producing high resolution images. SAR has the advantage of all-weather sensing and it has tremendous applications in areas such as the military, agriculture, oceanography, resource mapping, and so on. However, SAR image is contaminated by speckle which is multiplicative in nature, and its presence in the image makes image contents interpretation difficult. Also as tremendous amounts of data gathered from the SAR system increases, the storage capacity and transmission speed do not increase at the same rate. In this paper we present a SAR image despeckling and compression technique. In this technique, the K-Nearest Neighbour (KNN) algorithm is employed to modify the well-known Lee filter to improve its performance for SAR image despeckling. The despeckling method is used to address some of the shortcomings of existing SAR image despeckling filters. Existing speckle filters introduce blur when used to despeckle SAR images. In addition, feature and edge preservation problems also arise. With our method, a suitable number of nearest neighbour pixels within the sliding window can be selected for calculating the filtering parameters. With a 5×5 window size, the best result is obtained when only 15 out of the 25 pixels are used. The improved filter is then used to despeckle the SAR image before it is compressed using the Two-Dimensional Discrete wavelet Transform (2-D DWT). The wavelet transform coefficients are coded with the Set Partitioning in Hierarchical Trees (SPIHT) scheme with the removal of the arithmetic coding stage. It is evident, from the simulation results shown that better results are obtained when a SAR image is despeckled prior to compression.

关键词： Synthetic aperture radar image coding Speckle Discrete wavelet transforms image resolution

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Two level 2-DDWT convolution structure for high speed operation using Daubehies wavelet

Two level 2-DDWT convolution structure for high speed operat...

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International Conference on Electronics, Communication and Computing Technologies (ICECCT)

作者： V. Krushna Kanth P. Samundiswary Department of Electronics Engineering Pondicherry University Pondicherry India

ISBN: (纸本)9781479960866

The Discrete wavelet Transform (DWT) has a huge number of applications in science and engineering technology. It is used for signal coding, to represent a discrete signal in a more redundant form, often as a preconditioning for data compression. Practical applications can also be found in signal processing, digital communications and many others. There are several techniques available for DWT like orthogonal, bi-orthogonal, HAAR, Dual-Tree Complex wavelet Transform, and Newland transform. A multiplier-less based architecture on algebraic integer representation for computing the Daubechies6-tap wavelet transform is used for two level 2D-DWT as wavelet filters in image processing. This architecture improves on previous designs in a way that it minimizes the number of parallel 2-input adder circuits. In this paper the design is implemented for a two-level 2-D decomposition using a Xilinx Virtex-6 xc6vcx75t-2-ff484 field programmable gate array (FPGA) device operating at up to a maximum clock frequency of 344/168 MHz.

关键词： Discrete wavelet transforms Artificial neural networks Field programmable gate arrays Encoding Biological system modeling Complexity theory Delays

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wavelet Based Imperceptible Medical image Watermarking Using Spread-Spectrum

Wavelet Based Imperceptible Medical Image Watermarking Using...

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International Conference on Telecommunications and signal processing

作者： Basant Kumar Shishu Bind Kumar Digvijay Singh Chauhan Motilal Nehru National Institute of Technology Feroze Gandhi Institute of Engineering & Technology

ISBN: (纸本)9781479984992

This paper presents a spread-spectrum watermarking algorithm for embedding text watermark in to digital images in discrete wavelet transform (DWT) domain. The algorithm is applied for embedding text file represented in binary arrays using ASCII code into host digital radiological image for potential telemedicine applications. In order to enhance the robustness of text watermarks like patient identity code, BCH (Bose, Ray-Chaudhuri, Hocquenghem) error correcting code (ECC) is applied to the ASCII representation of the text watermark before embedding. Performance of the algorithm is analysed by varying the gain factor, subband decomposition levels, and length of watermark. Robustness of the scheme is tested against various attacks like compression, filtering, noise, sharpening, scaling and histogram equalization. Simulation results show that the proposed method achieves imperceptible watermarking for string watermarks. It is also observed that the use of BCH code improves the performance by reducing bit error rate (BER) performance.

关键词： BER BCH Discrete wavelet transform HVS Spread-spectrum Watermarking

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image super resolution scheme based on wavelet transform and its performance analysis

Image super resolution scheme based on wavelet transform and...

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International Conference on Computing, Communication & Automation (ICCCA)

作者： P. B. Chopade P. M. Patil Sinhgad College of Engineering Pune India KJ's Educational Institute Pune India

ISBN: (纸本)9781479988914

Super resolution is very useful and interesting area of research in image processing applications based on wavelet transform. Many algorithms have been developed by researchers based on Projection Onto Convex Set (POCS), Maximum-aposteriori (MAP) and Maximum Likelihood (ML). In this paper, we propose super resolution algorithm based on Stationary wavelet Transform (SWT) and Discrete wavelet Transform (DWT). Single frame super resolution can be achieved by use of different interpolation method but this scheme generates blur at the edges of images. Hence in this paper we relied on wavelet transform for super resolution algorithm with different orthogonal and bi-orthogonal filters. Quality aspect of image such as MSE, PSNR, SSIM and Correlation Coefficient are calculated with this proposed algorithm.

关键词： Discrete wavelet transforms Spatial resolution Interpolation signal resolution

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