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检索条件"任意字段=Conference on Wavelet Applications in Signal and Image Processing VII"

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Improving spatial resolution of infrared images by means of sensor fusion

Improving spatial resolution of infrared images by means of ...

引用

conference on Hybrid image and signal processing vii

作者： Li, J Sheng, YL Univ Laval Dept Phys COPL St Foy PQ G1K 7P4 Canada

ISBN: (纸本)0819436704

This paper presents a cooperative hierarchical fusion scheme based on "a trous" wavelet transformation for the fusion of Infrared and visible images. At first, the restoration algorithm of multi-frames is presented to filter image noise and to improve the detail information of the infrared image. Then both the infrared and the visible images are decomposed to multilayer wavelet planes, respectively. A hierarchical merging is used for feature selection of wavelet planes by taking the weighted average at each scale. Lastly, the inverse wavelet transformation is implemented from the approximation data of the infrared image and the fused wavelet coefficients at various scales. One visible and three-frame infrared images are used to test the performance of the proposed scheme. Experimental results show that the spatial resolution improvement of the infrared image can be cooperatively achieved by multi-frame image restoration and sensor fusion. The advantage of the proposed cooperative merging algorithm is that the salient detail information from both visible and infrared images is preserved. No artifacts such as the blocking effect exist in the merged result. Moreover, the proposed method allows use of a dyadic wavelet to merge different sensor data of nondyadic resolution in a simple and efficient approach.

关键词： hierarchical fusion wavelet planes multiresolution analysis degradation model restoration infrared image sequences

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Nonlinear Multi-Scale Statistical Identification Approach for Data processing Enhancing and Quantitative Study

Nonlinear Multi-Scale Statistical Identification Approach fo...

引用

IEEE International conference on Control applications/International Symposium on Intelligent Control

作者： Ye, Zhengmao Mohamadian, Habib Southern Univ Coll Engn Baton Rouge LA 70813 USA

ISBN: (纸本)9781424446018

Integration of the nonlinear approaches for system identification is proposed for spectral differentiation and object recognition in this research. Multi-scale nonlinear principal component analysis (NCA) has been implemented to analyze the individual components of approximations and details based on wavelet transform. Neural network training has been applied to NCA while both ID and 2D wavelet transform have been conducted across different scales. At each scale, the principal components are selected in order to reconstruct the intrinsic signal and image. This statistical identification approach is essential to enhance multivariate data processing. Case studies on signal and image processing are both conducted. In addition, quantitative measures are presented to analyze the nonlinear multi-scale approach from the objective perspectives.

关键词： Nonlinear Principal Component Analysis Discrete wavelet Transform signal processing image processing

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Statistical analysis of fMRI data using orthogonal filterbanks

Statistical analysis of fMRI data using orthogonal filterban...

引用

conference on wavelet applications in signal and image processing vii

作者： Feilner, M Blu, T Unser, M Swiss Fed Inst Technol Biomed Imaging Grp DMT IOA CH-1015 Lausanne Switzerland

ISBN: (纸本)0819432997

Functional magnetic resonance imaging (fMRI) is a recent technique that allows the measurement of brain metabolism (local concentration of deoxyhemoglobin using BOLD contrast) while subjects are performing a specific task. A block paradigm produces alternating sequences of images (e.g., rest versus motor task). In order to detect and localize areas of cerebral activation, one analyzes the data using paired differences at the voxel level. As an alternative to the traditional approach which uses Gaussian spatial filtering to reduce measurement noise, we propose to analyze the data using an orthogonal filterbank. This procedure is intended to simplify and eventually improve the statistical analysis. The system is designed to concentrate the signal into a fewer number of components thereby improving the signal-to-noise ratio. Thanks to the orthogonality property, we can test the filtered components independently on a voxel-by-voxel basis;this testing procedure is optimal for i.i.d. measurement noise. The number of components to test is also reduced because of down-sampling. This offers a straightforward approach to increasing the sensitivity of the analysis (lower detection threshold) while applying the standard Bonferroni correction for multiple statistical tests. We present experimental results to illustrate the procedure. In addition, we discuss filter design issues. In particular, we introduce a family of orthogonal filters which are such that any integer reduction m can be implemented as a succession of elementary reductions m(1) to m(p) where m = m(1) ... m(p) is a prime number factorization of m.

关键词： functional imaging fMRI statistical analysis medical imaging wavelet application filterbank

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LOGARITHMIC MULTIRESOLUTION ANALYSIS

LOGARITHMIC MULTIRESOLUTION ANALYSIS

引用

IEEE International conference on image processing (ICIP)

作者： Navarro, Laurent Jourlin, Michel Courbebaisse, Guy Ecole Natl Super Mines CIS EMSE CNRS UMR 5307LGF F-42023 St Etienne France Univ St Etienne Lab H Curien CNRS UMR 5516 St Etienne France UCB Lyon1 CREATIS CNRS UMR 5220INSERMU1044INSA Lyon Lyon France

ISBN: (纸本)9781479983391

Recently, a logarithmic image processing model called Symmetric Logarithmic image processing (S-LIP) has been investigated in the framework of the multiresolution analysis (MRA) performed by wavelet transform. The S-LIP model is an extension of the Logarithmic image processing (LIP) model. The motivation of this work is to implement classical wavelet applications in the S-LIP framework. The underlying idea is to take advantage of both the multiscale analysis performed by the wavelet transform and the logarithmic processing of the pixels' intensity by the S-LIP model. The S-LIP wavelet transform is introduced and applied to automatic denoising in order to highlight its intrinsic characteristics. As an illustration, signal-to-Noise Ratios for both the linear wavelet transform and S-LIP wavelet transform are calculated for different levels of Gaussian, Poisson, Speckle and salt-and-pepper noises.

关键词： wavelet Transform Logarithmic image processing Symmetric Logarithmic image processing Denoising

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wavelet signal processing applied to Optical Phase Conjugation

Wavelet signal processing applied to Optical Phase Conjugati...

引用

conference on wavelets - applications in signal and image processing IX

作者： Jones, KJ Rice Univ Dept Math Houston TX 77005 USA

ISBN: (纸本)0819441929

wavelet signal processing has demonstrated remarkable capabilities in reducing noise, achieving better resolution through edge detection and increasing data transmission by means of data compression. While wavelets are digital, another field, Optical Phase Conjugation (OPC), is analog and has been applied to similar problems: signal and image distortion reduction and optical data storage. wavelets have been applied to optical solitons, laser beam diagnostics, diode laser arrays, interferometry and optical correlators. wavelet signal processing will be applied to Optical Phase Conjugation to examine laser beam interaction in nonlinear crystals and remove distortion from input and output laser beams.

关键词： wavelet signal processing optical phase conjugation optical data storage noise reduction Morlet wavelets photorefractive memories

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image denoising using orthonormal finite ridgelet transform

Image denoising using orthonormal finite ridgelet transform

引用

conference on wavelet applications in signal and image processing viiI

作者： Do, MN Vetterli, M Ecole Polytech Fed Lausanne LCAV CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

This paper addresses the image denoising problem using a newly proposed digital image transform: the finite ridgelet transform (FRIT). The transform is invertible, non-redundant and achieved via fast algorithms. Furthermore this transform can be designed to be orthonormal thus indicating its potential in many other image processing applications. We then propose various improvements on the initial design of the FRIT in order to make it to have better energy compaction and to reduce the border effect. Experimental results show that the new transform outperforms wavelets in denoising images with linear discontinuities.

关键词： wavelets Discrete wavelet transforms Denoising Radon transform image denoising wavelet transforms Fourier transforms Radon Digital imaging image processing

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Edge-Based image Watermarking Method with Weighted Discrete Cosine Transform Coefficients 30

Edge-Based Image Watermarking Method with Weighted Discrete ...

引用

30th IEEE signal processing and Communications applications conference (SIU)

作者： Karakis, Rukiye Gurkahraman, Kali Sivas Cumhuriyet Univ Yazihm Muhendisligi Bolumu Sivas Turkey Sivas Cumhuriyet Univ Bilgisayar Muhendisligi Bolumu Sivas Turkey

ISBN: (纸本)9781665450928

In image watermarking, hybrid approaches increase imperceptibility and robustness. Also, a scaling factor is used, which should be optimized when combining the cover image and watermark. In this study, discrete wavelet transform and discrete cosine transform (DCT) were used together. The watermark-edge image was obtained by randomly inserting the watermark on the horizontal, vertical and diagonal edge points of the cover image detected with Sobel. The DCT frequency components of the watermark-edge image were weighted with a generated matrix and combined with the DCT of the cover image. According to the obtained results, the proposed method is imperceptible and robust to various attacks, especially JPEG compression and noise attacks.

关键词： image watermarking edge detection scaling factor discrete wavelet transform discrete cosine transform

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Pavement images Denoising with Cracks Detection and Classification Using 2D Discrete wavelet Transform and Savitzky-Golay Filters

Pavement Images Denoising with Cracks Detection and Classifi...

引用

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

作者： Hamici, Zoubir Obaidat, Turki I. Al-Suleiman Al Zaytonnah Univ Jordan Elect Engn Dept Amman Jordan Al Zaytonnah Univ Jordan Civil Engn Dept Amman Jordan

ISBN: (纸本)9781728133775

image processing has gained an increased usage and impact in modern pavement networks automatic distress severity classification (DSC). DSC defines priorities and maintenance resources optimum allocation in order to achieve a cost-effective rehabilitation process. This paper presents a novel computer vision algorithm having the ability to process, isolate and evaluate the distress severity level of a pavement. A pavement color image is converted to grayscale and then processed for image denoising of the granularity and complex texture that represent and artifact in cracks edge detection. The processing is achieved by a 2D dual-tree double density wavelet transform filter banks that significantly reduces the granularity noise while preserving the pavement cracks for edge detection. The 2D wavelet FIR filters perform analysis, soft thresholding then a synthesis of the image. The second step is then an edge detection process followed by morphological filtering and labeled components size-histogram filter to isolate false edges as residuals of denoising. A final step is performed by two Savitzky-Golay filters for the detection of longitudinal and transverse alligator cracks projections. A weighted score function with multiple parameters is used for DSC.

关键词： Computer vision wavelets filter-banks Denoising Savitzky-Golay Filters Pavement Cracks

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Fast algorithm for binary field wavelet transform for image processing

Fast algorithm for binary field wavelet transform for image ...

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International conference on image processing (ICIP 2001)

作者： Law, NF Liew, AWC Siu, WC Hong Kong Polytech Univ Dept Elect & Informat Engn Ctr Multimedia Signal Proc Hong Kong Hong Kong Peoples R China

ISBN: (纸本)0780367251

Lifting scheme for the real field wavelet transform has provided a new insight into its practical implementation. This paper shows that a similar scheme can be developed for the binary field wavelet transform. In particular, by using the Euclidean algorithm the binary filters can be decomposed into a finite sequence of simple lifting steps over the binary field. This provides an alternative method for the implementations of the binary field wavelet transform for image processing applications. It is found that the new implementation can reduce the number of arithmetic operations involved in the transform and allow an efficient in-place implementation structure.

关键词： image processing

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Improved Single image Super-resolution Using Sparsity and Structured Dictionary Learning in wavelet Domain

Improved Single Image Super-resolution Using Sparsity and St...

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21st signal processing and Communications applications conference (SIU)

作者： Nazzal, Mahmoud Ozkaramanli, Huseyin Eastern Mediterranean Univ Dept Elect & Elect Engn Mersin Turkey

ISBN: (纸本)9781467355636;9781467355629

This paper introduces a single-image super-resolution approach which is based on sparse representation over dictionaries learned in the wavelet domain. The diagonal detail subband learning and reconstruction is improved by designing two diagonal dictionaries;one for the diagonal and another for the anti-diagonal orientations. Four pairs (low resolution and high resolution) of subband dictionaries are designed. The sparse representation coefficients for the respective low and high resolution images are assumed to be the same. The proposed algorithm is compared with the leading super-resolution techniques and is shown to excel both visually and quantitatively, with an average PSNR raise of 0.82 dB over the Kodak set. Moreover, this algorithm is shown to significantly reduce the dictionary learning computational complexity by designing compactly sized structural dictionaries.

关键词： Dictionaries as Topic wavelet domain super-resolution Diagonal sparse representation High definition subband

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