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IEEE International Conference on signal and image processing applications (ICSIPA)

作者： Singh, Satendra Pal Bhatnagar, Gaurav Indian Inst Technol Jodhpur Dept Math Jodhpur Rajasthan India

ISBN: (纸本)9781509055593

In this paper, a robust image hashing framework is proposed using image normalization, discrete wavelet transform and singular value decomposition. The stressed motive of the proposed scheme is to obtain a randomize hash sequence which can be used for image authentication and database search. For this purpose, the image is first normalized followed by hash generation in the wavelet domain utilizing the properties of singular value decomposition (SVD). Experimental evaluations demonstrate that the proposed scheme is providing the better robustness and security.

关键词： Discrete wavelet transforms Shearing Robustness Hamming distance Authentication image processing

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Quality index evaluation of videos based on fuzzy interface system

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IET image processing 2017年第5期11卷 292-300页

作者： Al-Naji, Ali Lee, Sang-Heon Chahl, Javaan Univ South Australia Sch Engn Adelaide SA 5095 Australia Middle Tech Univ Coll Elect & Elect Engn Tech Baghdad Iraq Def Sci & Technol Grp Joint & Operat Anal Div Port Melbourne Vic 3207 Australia

Objective image quality assessment (IQA) is a challenge facing digital image and video processing systems because image quality is distorted during various applications, including restoration, compression, storage and transmission. Therefore, this study proposes a new methodology based on a fuzzy interface system called quality evaluation system (QES) to measure the total quality index (TQI) of input videos with many distorted situations. Nine quality metrics [peak signal-to-noise ratio, visual signal-to-noise ratio, weighted signal-to-noise ratio, structural similarity (SSIM), multi-scale SSIM, universal image quality index, visual information fidelity, information fidelity criterion and noise quality measure] were used as inputs for three fuzzy logic controller systems, and their outputs were set as inputs to another fuzzy logic controller system to obtain the TQI of the input video. This process contributes to obtain clear performance of the quality index of the input video despite the failure of some IQA methods in providing quality performance of the input video in some situations. The proposed QES is tested on four videos captured with different digital cameras under different noise levels. Furthermore, the authors evaluated the proposed QES on three databases (TID2008, TID2013 and LIVE) to improve the experimental results. In addition, the authors used wavelet decomposition and image de-noising to enhance the standard Eulerian video magnification technique. The proposed QES was also used to prove that the authors' magnification system has better magnification quality index than other magnification techniques.

关键词： video signal processing fuzzy control Gaussian noise image denoising wavelet transforms image enhancement TID2008 databases TID2013 databases LIVE databases wavelet decomposition image denoising standard Eulerian video magnification technique image blurring Poisson noise Gaussian noise quality performance fuzzy logic controller systems noise quality measure information fidelity criterion visual information fidelity universal image quality index multiscale SSIM structural similarity weighted signal-to-noise ratio visual signal-to-noise ratio peak signal-to-noise ratio TQI total quality index quality evaluation system image quality distortion video processing systems digital image processing systems objective IQA objective image quality assessment fuzzy interface system video quality index evaluation

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wavelet-based detection of transients in biological signals

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Proceedings of SPIE - The International Society for Optical Engineering 1994年 2303卷 105-117页

作者： Mzaik, Tahsin Jagadeesh, Jogikal M. The Ohio State Univ. Columbus OH USA

ISBN: (纸本)0819416274;9780819416278

This paper presents two multiresolution algorithms for detection and separation of mixed signals using the wavelet transform. The first algorithm allows one to design a mother wavelet and its associated wavelet grid that guarantees the separation of signal components if information about the expected minimum signal time and frequency separation of the individual components is known. The second algorithm expands this idea to design two mother wavelets which are then combined to achieve the required separation otherwise impossible with a single wavelet. Potential applications include many biological signals such as ECG, EKG, and retinal signals.

关键词： wavelet transforms

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The shiftable complex directional pyramid - Part II: Implementation and applications

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IEEE TRANSACTIONS ON signal processing 2008年第10期56卷 4661-4672页

作者： Nguyen, Truong T. Oraintara, Soontorn Univ Texas Arlington Dept Elect Engn Arlington TX 76019 USA

In Part I ["The shiftable complex directional pyramid-Part 1: Theoretical Aspects," IEEE TRANSACTIONS ON signal processing, vol. 56, no. 10, October 2008], we proposed a novel image decomposition called the shiftable complex directional pyramid. The shiftable, multiresolution and multidirectional image decomposition is constructed by the pyramidal dual-tree directional filter bank (PDTDFB). In this Part II, we consider the design and implementation issues of the PDTDFB and its applications in image processing. The PDTDFB is composed of a multiresolution filter bank (FB) and a pair of directional filter banks (DFB);the design of each FB is considered separately. The binary tree structure of the DFB is modified to minimize the phase delay factor in order to reduce the border artifact in case symmetric extension is used. The filters presented in this paper are designed in frequency domain, and approximated by finite-impulse-response (FIR) filters. Numerical experiments show that the filters from the dual branches approximate the Hilbert transform of those from the primal ones, and the resulting PDTDFB yields acceptable shiftability. The shiftable pyramid decomposition is then tested in image processing applications, including image denoising, texture retrieval and seismic image migration.

关键词： complex wavelet directional decomposition directional filter bank dual-tree DWT multiresolution representation

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wavelet-based image interpolation using multilayer perceptrons

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NEURAL COMPUTING & applications 2005年第1期14卷 1-10页

作者： Huang, YL Tunghai Univ Dept Comp Sci & Informat Engn Taichung 407 Taiwan

Changing the resolution of digital images and video is needed image processing systems. In this paper, we present nonlinear interpolation schemes for still image resolution enhancement. The proposed neural network interpolation method is based on wavelet reconstruction. With the wavelet decomposition, the image signals can be divided into several time-frequency portions. In this work, the wavelet decomposition signal is used to train the neural networks. The pixels in the low-resolution image are used as the input signal of the neural network to estimate all the wavelet sub-images of the corresponding high-resolution image. The image of increased resolution is finally produced by the synthesis procedure of wavelet transform. In the simulation, the proposed method obtains much better performance than other traditional methods. Moreover, the easy implementation and high flexibility of the proposed algorithm also make it applicable to various other related problems.

关键词： interpolation image resampling neural network wavelet transform subband filtering

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Subband coding and noise reduction in multiresolution analysis frames

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Proceedings of SPIE - The International Society for Optical Engineering 1994年 2303卷 154-165页

作者： Benedetto, John J. Li, Shidong Univ. of Maryland/Coll. Park and MITRE Corp. Coll. Park MD USA

We consider the effect of the quantization noise introduced by coding at subbands. We demonstrate that significant noise reduction is achieved by using wavelet frames and their associated filter banks in a subband sig... 详细信息

ISBN: (纸本)0819416274;9780819416278

关键词： image coding

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wavelet-based pavement distress detection and evaluation

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OPTICAL ENGINEERING 2006年第2期45卷

作者： Zhou, J Huang, PS Chiang, FP SUNY Stony Brook Dept Mech Engn Stony Brook NY 11794 USA

An automated pavement inspection system consists of image acquisition and distress image processing. The former is accomplished with imaging sensors, such as video cameras and photomultiplier tubes. The latter includes distress detection, isolation, classification, evaluation, segmentation, and compression. We focus on wavelet-based distress detection, isolation, and evaluation. After a pavement image is decomposed into different-frequency subbands by the wavelet transform, distresses are transformed into high-amplitude wavelet coefficients and noise is transformed into low-amplitude wavelet coefficients, both in the high-frequency subbands, referred to as details. Background is transformed into wavelet coefficients in a low-frequency subband, referred to as approximation. First, several statistical criteria are developed for distress detection and isolation, which include the high-amplitude wavelet coefficient percentage (HAWCP), the high-frequency energy percentage (HFEP), and the standard deviation (STD). These criteria are tested on hundreds of pavement images differing by type, severity, and extent of distress. Experimental results demonstrate that the proposed criteria are reliable for distress detection and isolation and that real-time distress detection and screening is currently feasible. A norm for pavement distress quantification, which is defined as the product of HAWCP and HFEP, is also proposed. Experimental results show that the norm is a useful index for pavement distress evaluation. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

关键词： wavelet transform automated pavement inspection pavement distress image processing distress detection and isolation distress evaluation

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wavelet-based multifractal analysis of 1-D and 2-D signals: New results

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ANALOG INTEGRATED CIRCUITS AND signal processing 2011年第1期69卷 3-15页

作者： Ouahabi, A. Femmam, S. Polytech Engineers Sch EPF Sceaux France Univ Tours Grad Sch Engn Tours France UHA Univ Mulhouse France Univ Tours Ecole Polytech Tours France

During the past decade, new tools stemming from fractal geometry and wavelet analysis are meeting with great success in signal image processing. This paper will focus on these two topics: wavelets and Multifractal. Both themes evolved towards self contained theories, and yet, a host of reasons justify for coupling them in same applications. It is well known that both analyses share the same conceptual backbone of "scale'': it is the "mathematical zoom'' commonly associated to wavelet analysis and it is the "scaling laws'' that underlie multifractal structures. Very naturally then, wavelets stood as a privileged tool for analyzing and characterizing multifractal signals and images. Hence, the purpose of this paper is to illuminate some of the issue involved in taking advantage of the current advances in wavelets and multifractals analysis. We discuss continuous, discrete, orthogonal wavelets and present applications to fracture processes and medical ultrasound imaging.

关键词： Multifractal spectrum Fracture signal wavelet Singularity Ultrasound imaging Tissue characterization

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applications OF COMPLEX-VALUED wavelet TRANSFORMS TO SUBBAND DECOMPOSITION

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IEEE TRANSACTIONS ON signal processing 1993年第12期41卷 3566-3568页

作者： LAWTON, W Institute of Systems Science National University of Singapore Singapore

A method for constructing complex valued linear phase FIR conjugate quadrature filters and associated wavelet bases is described. Each filter is derived by replacing certain zeros of a real valued FIR conjugate quadrature filter by their reciprocal conjugates. The derived filters have the same frequency response magnitudes as the original filters and their liner phase property permits the use of symmetrization in subband decomposition to avoid border discontinuities that result from signal periodization. Subband decomposition and reconstruction using both a length 6 filter associated with a Daubechies wavelet bases and a related length 6 complex valued linear phase filter are compared to illustrate the reduced border effects.

关键词： wavelet transforms Finite impulse response filter Nonlinear filters image reconstruction Displays Frequency response Solids Reflection Quantization

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A Dual Chaotic Encryption Method for Lightweight Infrared image

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MOBILE NETWORKS & applications 2022年第2期27卷 767-774页

作者： Chen, Zhi-hua Srivastava, Gautam Guangdong Polytech Normal Univ Network Informat Ctr Guangzhou 510665 Peoples R China Brandon Univ Dept Math & Comp Sci Brandon MB Canada China Med Univ Res Ctr Interneural Comp Taichung Taiwan

When the existing methods are used to encrypt the lightweight infrared image, there is no denoising processing for the lightweight infrared image, which has the problems of low image signal-to-noise ratio, low encryption efficiency and poor encryption effect. A dual chaotic encryption method for lightweight infrared image is proposed. The discrete orthogonal wavelet transform is used to process the lightweight infrared image. The wavelet coefficients of the lightweight infrared image are estimated by improving the block singular value decomposition. The estimated high-frequency image and low-frequency image are transformed by inverse wavelet transform to complete the denoising of the lightweight infrared image. The wavelet coefficients are estimated by threshold method or minimum mean square error method, and then the noise free lightweight infrared image is obtained by inverse wavelet transform. The lightweight infrared image is encrypted by double scrambling of pixel position and bit, and the dual chaotic encryption of lightweight infrared image is realized. The experimental results show that the security coefficient of the image encrypted by this method is more than 0.8. This method has high image signal-to-noise ratio, high encryption efficiency and good encryption effect.

关键词： Lightweight infrared image image denoising image encryption Pixel position scrambling Bit scrambling

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