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A novel multimodal compression scheme based on a spiral insertion function in the wavelet domain

A novel multimodal compression scheme based on a spiral inse...

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2012 11th International conference on Information Science, signal processing and their applications, ISSPA 2012

作者： Boubchir, Larbi Brahimi, Tahar Fournier, Regis Naït-Ali, Amine Université Paris-Est Créteil 61 avenue du Général de Gaulle 94010 Créteil France Signal Processing Research Center Qatar University College of Engineering Doha Qatar

ISBN: (纸本)9781467303828

This paper presents a new variant of multimodal compression scheme based on a spiral insertion function in the wavelet domain. The main idea consists of inserting a decomposed signal into a decomposed image prior to a joint SPIHT compression process. The insertion phase is achieved in the detail sub-bands of the wavelet decomposition. The evaluation is assessed on both natural and medical images using objective and subjective comparison criteria. The experimental results showed the effectiveness of the proposed approach to obtain significant gains in terms of reconstructed signal (PRD %) and image (PSNR). © 2012 IEEE.

关键词： wavelet decomposition

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wavelet based compression and denoising of convolution operators

Wavelet based compression and denoising of convolution opera...

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conference on wavelet applications in signal and image processing VI

作者： Kompella, N Machiraju, R Choudhary, A Skjellum, A Mississippi State Univ NSF Engn Res Ctr Mississippi State MS 39762 USA

ISBN: (纸本)0819429139

In highly computationally intensive fields such as signal processing, image processing, computer graphics and visualization, much of the CPU time is spent in computing various transforms on the typically large data sets which may also contain noise. Though extensive work has been reported on the de-noising and subsequent compression of the data, little of it has been reported on the de-noising and subsequent compression of the operators. Moreover, in the work reported so far, thresholding, which is essential for achieving denoising, has not been based on a specific criterion. In the present work, we propose modifications to this approach which result in significant savings in the computational cost of the associated transformations. We present wavelet based approaches to compress different operators. We present two methods to accomplish this. In the first method, we first apply a non-standard wavelet transform on the operator represented in its matrix form. This step is followed by an adaptive thresholding scheme of Donohoe and Johnstone(3), which results in the de-noised form of the operator. In the second method, the original matrix representation of the operator is split into two sparse diagonal dominant matrices, one in the spatial domain and the other in the wavelet domain. Although, there is a need to use the original signal in the spatial domain, the resulting decomposition actually requires only a portion of the operators. More importantly, the decomposition results in representations with very little total error. We find that the computational complexity of the transformation, using these methods, reduces to O(N) as opposed to O(N-2) (where N is the size of the data vector) observed with using the original, denser representation of the operator. In particular, Method 2 allows even more expedient processing of signals with greater accuracy. Hence, many transformations with operators can be represented in a diagonally dominant matrix form resulting in signifi

关键词： signal processing operators thresholding denoising compression

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image denoising using a neural network based non-linear filter in wavelet domain

Image denoising using a neural network based non-linear filt...

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2005 IEEE International conference on Acoustics, Speech, and signal processing, ICASSP '05

作者： Zhang, S. Salari, E. Dept. of Computer Science Eastern Kentucky University Richmond KY 40475 Dept. of Electrical Engineering and Computer Science University of Toledo Toledo OH 40606

ISBN: (纸本)0780388747

images are often corrupted as a result of various factors that can occur during acquisition and transmission processes. image denoising is aimed at removing or reducing the noise so that a good-quality image can be obtained for various applications. This paper presents a neural network based denoising method implemented in the wavelet transform domain. In this method, a noisy image is first wavelet transformed into four subbands, then a trained layered neural network is applied to each subband to generate noise-removed wavelet coefficients from their noisy ones. The denoised image is thereafter obtained through the inverse transform on the noise-removed wavelet coefficients. Simulation results demonstrate that this method is very efficient in removing the noise. Compared with other methods performed in wavelet domain, it requires no a priori knowledge about the noise and needs only one level of signal decomposition to obtain very good denoising results. © 2005 IEEE.

关键词： image processing

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Proceedings of SPIE - wavelets: applications in signal and image processing X

Proceedings of SPIE - Wavelets: Applications in Signal and I...

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wavelets: applications in signal and image processing X

The proceedings contains 47 papers from the conference of SPIE - wavelets: applications in signal and image processing. The topics discussed include: a class of heavy-tailed multivariate non-Gaussian probability models for wavelet coefficients;iterative projective wavelet methods for denoising;interpolation and denoising of piecewise smooth signals by wavelet regularization;adaptive wavelet thresholding for multichannel signal estimation;resolution enhancement and sampling with wavelets and footprints;multiscale likelihood analysis and image reconstruction;harmonic spline series representation of scaling functions and armlets and balanced multiwavelets.

关键词： image analysis

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A Novel image Fusion Algorithm Based on Morphological wavelet Transforms via Lifting

A Novel Image Fusion Algorithm Based on Morphological Wavele...

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IEEE International conference on signal processing, Communications and Computing (ICSPCC)

作者： Shen Zheng-yan Henan Police Coll Dept Criminal Sci & Technol Zhengzhou Peoples R China

ISBN: (纸本)9781479952748

In order to improve the image analysis ability in some practical applications, an image fusion algorithm was proposed. This algorithm combined information from multiple images of the same scene in pixel level. Firstly, a group of lifting morphological wavelets for image fusion was discussed. Then using one of the schemes, multiple images were shift in different direction and decomposed respectively. Next, the transform coefficients were processed according to certain fusion criterion and some fusion results could be obtained through inverse transform and inverse displacement. Finally, such fused images were filtered to be one image we need. Computer simulation shows this algorithm in morphological wavelet domain can fuse grayscale images or color images effectively. Compared with the conventional wavelet transform, it gets a more complete and clearer scene.

关键词： Morphological wavelet multi-resolution analysis lifting scheme image processing image fusion

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Lowering frame-buffering requirements of 3-D wavelet transform coding of interactive video

Lowering frame-buffering requirements of 3-D wavelet transfo...

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International conference on image processing (ICIP'99)

作者： Khalil, Hosam Atiya, Amir F. Shaheen, Samir I. Univ of California Santa Barbara United States

In this paper, we present a 3-D wavelet compression technique for image sequences in video conferencing applications. One of the main requirements for such applications is that the delay has to be within some acceptable limit. When applying wavelet decomposition in the temporal direction, we must store a large number of frames so that such a decomposition can be effective. But this translates into a correspondingly large algorithmic delay. A technique to avoid this obstacle will be proposed. The basic idea is to overlap the decomposition with previous frames that have already been transmitted and selectively transmitting only the new wavelet coefficients.

关键词： image coding

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Adaptive wavelet transform algorithm for image compression applications

Adaptive wavelet transform algorithm for image compression a...

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conference on applications of Digital image processing XXVI

作者： Pogrebnyak, O Ramírez, PM Inst Politecn Nacl CIC Mexico City 07738 DF Mexico

ISBN: (纸本)0819450766

A new algorithm of locally adaptive wavelet transform is presented. The algorithm implements the integer-to-integer lifting scheme. It performs an adaptation of the wavelet function at the prediction stage to the local image data activity. The proposed algorithm is based on the generalized framework for the lifting scheme that permits to obtain easily different wavelet coefficients in the case of the ((N) over tilde , N) lifting. It is proposed to perform the hard switching between (2, 4) and (4, 4) lifting filter outputs according to an estimate of the local data activity. When the data activity is high, i.e.. in the vicinity of edges, the (4, 4) lifting is performed. Otherwise. in the plain areas. the (2,4) decomposition coefficients are calculated. The calculations are rather simples that permit the implementation of the designed algorithm in fixed point DSP processors. The proposed adaptive transform possesses the perfect restoration of the processed data and possesses good energy compactation. The designed algorithm was tested on different images. The proposed adaptive transform algorithm can be used for image/signal compression and noise suppression.

关键词： image processing wavelets lifting scheme lossless compression

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PRIVACY PROTECTED image DENOISING WITH SECRET SHARES

PRIVACY PROTECTED IMAGE DENOISING WITH SECRET SHARES

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19th IEEE International conference on image processing (ICIP)

作者： SaghaianNejadEsfahani, Sayed M. Luo, Ying Cheung, Sen-ching S. Univ Kentucky Dept Elect & Comp Engn Lexington KY 40506 USA

ISBN: (纸本)9781467325332;9781467325349

The proliferation of digital cameras, wireless networks and distributed computing make sharing of visual data easier than ever. Such casual exchange of data, however, has increasingly raised questions on how sensitive visual information can be protected. Encrypted-domain signal processing techniques based on homomorphic encryption and garbled circuits are increasingly applied for such applications. Their high computation and communication complexity, however, are not suitable for pixel-level processing. In this paper, we propose an alternative approach of using information-theoretically secure protocols over multiple non-colluding semi-honest computing agents. The proposed protocols are based on classical Shamir's secret sharing scheme which supports multiplication and addition in the random-share domain. We extend the sharing scheme to handle other fundamental signal processing operations and use them to develop a novel privacy-protected wavelet denoising scheme over three computing agents. Our experimental results demonstrate the viability of using information-theoretic secure protocols to safeguard privacy in distributed pixel-level processing.

关键词： secret sharing wavelet denoising

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Multiresolution wavelet decomposition to merge Landsat TM and SPOT panchromatic data

Multiresolution wavelet decomposition to merge Landsat TM an...

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2004 3rd International conference on Computational Electromagnetics and Its applications

作者： Wu Yan Li Ming LiaoGuisheng National Key Lab.Of Radar signal processing Xidian Univ. School of Electronics Engineering Xidian Univ

ISBN: (纸本)0780385624

A new algorithm is developed to merge a high-resolution panchromatic image and a low-rcsohition multi-spcctral image based on the combination of multi-resolution wavelet decomposition and the IHS *** high-resolution panchromatic image is firstly ciecornposed to the wavelet planes,then the region is divided by edge information from the wavelet planes and the intensity component from multi-spectral image is merged by fusion operator in different *** proposed method is compared with the IHS and the MWT *** experimental results show that the proposed method can achieve better fusion performance in combining and preserving spectral-spatial information.

关键词： image fusion,wavelet plane,Fusion operator IHS transform

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IMPROVING MESH-BASED MOTION COMPENSATION BY USING EDGE ADAPTIVE GRAPH-BASED COMPENSATED wavelet LIFTING FOR MEDICAL DATA SETS

IMPROVING MESH-BASED MOTION COMPENSATION BY USING EDGE ADAPT...

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

作者： Lanz, Daniela Kaup, Andre Friedrich Alexander Univ Erlangen Nurnberg FAU Multimedia Commun & Signal Proc Cauerstr 7 D-91058 Erlangen Germany

ISBN: (纸本)9781509041176

Medical applications like Computed Tomography (CT) or Magnetic Resonance Tomography (MRT) often require an efficient scalable representation of their huge output volumes in the further processing chain of medical routine. A downscaled version of such a signal can be obtained by using image and video coders based on wavelet transforms. The visual quality of the resulting lowpass band, which shall be used as a representative, can be improved by applying motion compensation methods during the transform. This paper presents a new approach of using the distorted edge lengths of a mesh-based compensated grid instead of the approximated intensity values of the underlying frame to perform a motion compensation. We will show that an edge adaptive graph-based compensation and its usage for compensated wavelet lifting improves the visual quality of the lowpass band by approximately 2.5 dB compared to the traditional mesh-based compensation, while the additional filesize required for coding the motion information doesn't change.

关键词： Discrete wavelet Transforms Motion Compensation Scalability signal processing on Graphs Computed Tomography

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