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Digital image Watermarking Using Multilevel wavelet Decomposition and Human Visual System

Digital Image Watermarking Using Multilevel Wavelet Decompos...

引用

International conference on Information Science and applications (ICISA)

作者： Zahoor Jan Muhammad Khalid Anwar M. Mirza Fouzia Jabeen Almas Abbasi Zabie Tarin Alwina Durrani Department of Computer Science Abdul Wali Khan University Mardan Pakistan Department of Computer Science Government College of Management Sciences Peshawar Pakistan Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Shaheed Benazir Bhutto Women University Peshawar Pakistan Faculty of computer Science and information Technology University of Malaya Malaysia

In this modern world Digital watermarking is of prime importance. This has increased the demand for copyright protection. Digital watermarking is a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. In this paper a non-blind watermarking has been proposed that embed a randomly generated binary numbers as watermark. Human Visual System (HVS) has been used to embed the watermark below the detection threshold (JND). High quality of robustness and imperceptibility are achieved through Just Noticeable Difference (JND) base selection of the detail coefficients. The experimental results show that the proposed technique is more resistant against all types of common signal processing operations and geometric attacks.

关键词： Watermarking Robustness Low pass filters image coding Discrete wavelet transforms

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Denoising one-dimensional signals with curvelets and contourlets

Denoising one-dimensional signals with curvelets and contour...

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IEEE National conference on Aerospace and Electronics (NAECON)

作者： Ryan Moore Soundararajan Ezekiel Erik Blasch Kate Gleason College of Engineering Rochester Institute of Technology Rochester NY Computer Science Indiana University of Pennsylvania Indiana PA Information Directorate Air Force Research Laboratory Rome NY

Fast Fourier Transforms (FFTs) and Discrete wavelet Transformations (DWTs) have been routinely used as methods of denoising signals. DWT limitations include the inability to detect contours, curves and directional information of multi-dimensional signals. In the past decade, two new approaches have surfaced: curvelets, developed by Candès; and contourlets, developed by Do et al. The typical applications of contourlets and curvelets include two-dimensional image data denoising. We explore the use of curvelets and contourlets to the one-dimensional (1D) denoising problem. Working with seismic data, we introduce various types of data noise and the wavelet, curvelet, and contourlet transforms are applied to each signal. We tested multiple decomposition levels and different thresholding values. The benchmark for determining the effectiveness of each transform is the peak signal-to-noise ratio (PSNR) between the original signal and the denoised signal. The proposed denoising methods demonstrate contourlets and curvelets as a viable alternative to the DWT and FFT during signal processing. The initial results indicate that the contourlet and curvelet methods yield a higher PSNR and lower error than the DWT and FFT for 1D data.

关键词： Discrete wavelet transforms PSNR Noise reduction Measurement

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Atmospheric correction of remotely sensed multispectral satellite images in transform domain

Atmospheric correction of remotely sensed multispectral sate...

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International conference on Advanced Computing, ICAC

作者： S. Gandhimathi Usha S. Vasuki Gowri Ariputhiran Velammal College of Engineering and Technology Madurai Tamil Nadu IN Department of ECE Velammal College of Engineering and Technology Madurai India

Remote sensing data provides much essential and critical information for monitoring many applications such as change detection, image fusion and land cover classification. Remotely sensed images are degraded due to the atmospheric effects. The atmospheric correction is one of the important pre processing steps to extract full spectral information from the remotely sensed images. In this paper, transform domain approaches are presented for the removal of atmospheric influences. Soft thresholding technique is adopted in wavelet transform method and gaussian high pass filter is used in homomorphic filtering. The results are tested on Landsat image consisting of 7 multispectral bands and their performance is evaluated using visual and statistical measures. The comparative analysis is done based on statistical parameters such as mean square error (MSE), peak signal to noise ratio (PSNR). Our result shows that wavelet transform is better for the removal of atmospheric effects than homomorphic filtering.

关键词： Discrete wavelet transforms Filtering Remote sensing Atmospheric waves Satellites PSNR

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Improving in Spectral Resolution for Closely-Spaced Targets Based on MUSIC Algorithm

Improving in Spectral Resolution for Closely-Spaced Targets ...

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International conference on Artificial Intelligence and image processing(ICAIIP’2012);International conference on Innovations in Electrical and Electronics Engineering(ICIEE’2012);International conference on Mechanical,Automobile and Biodiesel Engineering(ICMABE’2012);International conference on History,Literature and Management(ICHLM’2012);International conference on Agriculture,Chemical and Environmental Sciences(ICACES’2012);International conference on Biological and Medical applications(ICBMA’2012)

作者： M.Pourahmadi Department of Electrical Engineering Yazd branchIslamic Azad University

The multiple signal classification (MUSIC) method is severely based on the number of singular values of a multistatic response matrix (or signal subspace rank).In this paper we show that in the presence of multiple scattering between the targets,some singular values will greatly decrease and combine with the noise ones,so the performance of the most popular MUSIC methods degrades and even fails to estimate closely spaced target locations because of a reduction in signal *** such a case,we introduce a method to eliminate ambiguity in determining the number of scatterers employing a pre-processing step by two methods:discrete stationary wavelet transform (DSWT) and empirical mode decomposition (EMD).The DSWT is developed on the basis of features of the reflection coefficient between the *** application of this algorithm to measurement data,shows its superiority over the *** results indicate that MUSIC+DSWT yields accurate estimation of the target locations,even when there exist considerable noise and multiple scattering in the received signal.

关键词： MUSIC algorithm,wavelet transform,spectral resolution,microwave imaging.

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An efficient VLSI architecture for 2-D dual-mode SMDWT

An efficient VLSI architecture for 2-D dual-mode SMDWT

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IEEE International conference on Networking, Sensing and Control

作者： Chih-Hsien Hsia Jen-Shiun Chiang Shih-Hao Chang National Taiwan University of Science and Technology Taipei TW Tamkang University Taipei TW National Taiwan University Taipei TW

ISBN: (纸本)9781467351980

In this paper, we propose a highly efficient VLSI architecture for 2-D dual-mode (supporting 5/3 and 9/7 lifting-based) Symmetric Mask-based Discrete wavelet Transform (SMDWT) to improve the critical issue of the 2-D Lifting-based Discrete wavelet Transform (LDWT), and then obtains the benefit of low-latency reduced complexity, and low transpose memory. The SMDWT also has the advantages of reduced complexity, regular signal coding, short critical path, reduced latency time, and independent subband coding processing. The transpose memory requirement of the N×N is 9N. The architecture is based on the parallel and folding scheme processing to achieve higher hardware utilization ratio and reduce the silicon area. It is suitable for Very Large Scale Integration (VLSI) implementation and can be applied to real-time operating of computer vision applications.

关键词： Discrete wavelet transforms CMOS integrated circuits CMOS technology Very large scale integration Irrigation Biomedical imaging image recognition

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wavelet coding of polygonal mesh data based on triangular lattice structure with expanded nodes

Wavelet coding of polygonal mesh data based on triangular la...

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IEEE International conference on image processing

作者： M. Tsunoda T. Terasaki K. Fukuda A. Kawanaka Department of Electrical and Electronics Engineering Faculty of Science and Technology Sophia University Japan

Efficient representations of a 3D object shape and its textural data have attracted wide attention for the transmission of computer graphics data and for interactive design in manufacturing. Polygonal mesh data, which consist of connectivity information, geometric data and textural data are often used for representing a 3D object in many applications. We propose a compression method for polygonal mesh data by structuring its geometric and textural data on a triangular lattice with expanded nodes. The structuralized geometric and textural data are compressed using a 2D signal coding method. Experimental results following from the application of the new method to polygonal mesh data show that the proposed scheme performs efficiently.

关键词： Lattices Shape Computer graphics Surface texture Geometry Tree graphs Data engineering Design engineering Computer aided manufacturing Application software

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Mathematical analysis of the energy compaction affected by the dimensionality of Karhunen-Lòeve transform

Mathematical analysis of the energy compaction affected by t...

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IEEE International conference on image processing

作者： Yukihiro Bandoh Hiroki Ohbayashi Seishi Takamura Kazuto Kamikura Yoshiyuki Yashima NTT Cyber Space Laboratories NTT Company Limited Yokosuka Kanagawa Japan Faculty of Sciences Kyushu University Fukuoka Japan

ISBN: (纸本)9781424456536;9781424456543

Transform coding is a essential tool for picture coding applications, and coding schemes that can achieve high energy compaction are essential. In terms of energy compaction, Karhunen-Loeve transform (KLT) is known to be optimal. The energy compaction provided by KLT depends on the statistical property of the input signal and the dimensionality of KLT. However, the quantitative effect of KLT dimensionality on energy compaction has not been clarified. This paper establishes a mathematical model of the relationship among the dimensionality of KLT and the energy compaction of the transform coefficients, using mathematical tools in quantum information theory.

关键词： Mathematical analysis Compaction Karhunen-Loeve transforms Discrete cosine transforms Mathematical model Discrete transforms Transform coding Discrete wavelet transforms Quantum mechanics Information theory

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Zero Reference based Low-light Enhancement with wavelet Optimization

Zero Reference based Low-light Enhancement with Wavelet Opti...

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IEEE conference on Advanced Video and signal Based Surveillance (AVSS)

作者： Vivek Deshmukh Adinath Dukre Ashutosh Kulkarni Prashant W. Patil Santosh Kumar Vipparthi Subrahmanyam Murala Anil Balaji Gonde Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India CVPR Lab Indian Institute of Technology Ropar India Indian Institute of Technology Guwahati India CVPR Lab School of Computer Science and Statistics Trinity College Dublin Ireland

ISBN: (数字)9798350374285

ISBN: (纸本)9798350374292

images captured in low light conditions usually suffer from poor visibility, a high amount of noise, and little information stored in the dark image, which has a negative impact on subsequent processing for outdoor computer vision applications. Presently, numerous deep learning based methods achieved superior performance with multi-exposure paired training data or additional information. However, obtaining multi-exposure data samples is a tedious task in real-time scenarios. To mitigate this challenge, we propose a zero reference based learnable wavelet approach without multi-exposure paired training data requirement for low-light image enhancement. Our proposed approach generates the low light image and learns to project an image into noise free similar looking image, then we enhance the image using retinex theory. Further, we have proposed learnable wavelet block to remove the hidden noise amplified while enhancement. We introduce Gaussian-based supervision to improve the smoothness of the image. Extensive experimental analysis on synthetic as well as real-world images, along with thorough ablation study demonstrate the effectiveness of our proposed method over the existing state-of-the-art methods for low-light image enhancement. The code is provided at https://***/vision-lab-sggsiet/Zero-Reference-based-Low-light-Enhancement-with-wavelet-Optimization.

关键词： Training Reflectivity Deep learning Computer vision Surveillance Noise Training data

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Optimal JPEG2000 encoder mechanism for low delay and efficient distribution of HDTV programs

Optimal JPEG2000 encoder mechanism for low delay and efficie...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： S. Naito A. Koike S. Matsumoto KDDI Research and Development Laboratories Inc. Kamifukuoka Saitama Japan

Motion JPEG2000 has been developed as a new video coding standard for motion pictures, utilizing the still image coding standard JPEG2000. Motion JPEG2000 specifies a normative bitstream syntax that the decoder must recognize and allows flexible selection of detailed coding parameters at the encoder. The compression performance largely depends, therefore, on the encoder design. However, the simple implementation of JPEG2000 encoder might cause picture quality degradation due specifically to wavelet image coding of interlaced TV signals and unsatisfactory bit assignments. That degradation might then become conspicuous in subjective picture quality especially during low bit-rate coding. To overcome this problem, we investigated an optimal design for a Motion JPEG2000 encoder that can be used for primary distribution applications of HDTV programs, assuming that the available bit-rate is approximately 50 Mbps. Our study introduces advanced key technologies not yet recognized officially. Coding experiments using those technologies confirmed that a significant coding gain was achieved versus conventional encoding schemes.

关键词： Delay HDTV Transform coding image coding Standards development Degradation Video coding Motion pictures Decoding TV

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Improvements to SPIHT for Lossless image Coding

Improvements to SPIHT for Lossless Image Coding

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International conference on Information and Communication Technologies: From Theory to applications, ICTTA

作者： T. Brahimi A. Melit F. Khelifi D. Boutana Department of Electronic Engineering Faculty of Engineering Science University of Jijel Algeria Queen''s University Belfast UK

The SPIHT (set partitioning in hierarchical trees) algorithm has attracted great attention in recent years as a technique for image coding. Not only does it give good objective and subjective performance, it is also simple and efficient. In this paper we propose an enhanced image lossless image compression that is based on SPIHT. The most important modification in this algorithm is the addition of a simple modification to the set of type A with a new test on the threshold. Our experiments show that this improvement increases the performance of lossless image coding for all standard test images

关键词： image coding wavelet transforms Testing image resolution Decoding Partitioning algorithms Performance loss signal processing algorithms Scalability Video compression

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